1 00:00:00,040 --> 00:00:02,460 The following content is provided under a Creative 2 00:00:02,460 --> 00:00:03,870 Commons license. 3 00:00:03,870 --> 00:00:06,910 Your support will help MIT OpenCourseWare continue to 4 00:00:06,910 --> 00:00:10,560 offer high quality educational resources for free. 5 00:00:10,560 --> 00:00:13,460 To make a donation or view additional materials from 6 00:00:13,460 --> 00:00:16,036 hundreds of MIT courses, visit mitopencourseware at 7 00:00:16,036 --> 00:00:17,286 ocw.mit.edu. 8 00:00:28,240 --> 00:00:30,990 PROFESSOR: In some ways, I won't be able to compete with 9 00:00:30,990 --> 00:00:33,610 live demonstrations of children from last week. 10 00:00:33,610 --> 00:00:37,040 But I will try to talk about adult development. 11 00:00:37,040 --> 00:00:40,760 And we will really sweep through your minds and brains 12 00:00:40,760 --> 00:00:45,890 from when you were not yet born until you're going to be 13 00:00:45,890 --> 00:00:47,590 in your '90s. 14 00:00:47,590 --> 00:00:54,540 So here's your life from the beginning to the end viewed in 15 00:00:54,540 --> 00:00:54,980 different ways. 16 00:00:54,980 --> 00:00:57,250 And we'll touch on a number of different topics. 17 00:00:57,250 --> 00:00:59,930 So you know this question about people have talked for a 18 00:00:59,930 --> 00:01:03,210 long time about the development that one goes 19 00:01:03,210 --> 00:01:04,349 throughout one's life. 20 00:01:04,349 --> 00:01:06,320 What walks on four legs in the morning, two legs in the 21 00:01:06,320 --> 00:01:07,350 afternoon, three legs in the evening? 22 00:01:07,350 --> 00:01:10,030 You know the answer to this, right? 23 00:01:10,030 --> 00:01:11,330 People. 24 00:01:11,330 --> 00:01:14,040 They're crawling, they're standing up, and then 25 00:01:14,040 --> 00:01:15,030 you get to my age. 26 00:01:15,030 --> 00:01:17,200 And we need an extra little prop to move around 27 00:01:17,200 --> 00:01:18,880 successfully. 28 00:01:18,880 --> 00:01:21,880 So sort of thinking about this, that different things 29 00:01:21,880 --> 00:01:24,460 matter to people at different ages, that there's different 30 00:01:24,460 --> 00:01:27,300 priorities, different ways of thought. 31 00:01:27,300 --> 00:01:29,640 Erik Erickson is often given credit for trying to 32 00:01:29,640 --> 00:01:31,170 articulate that. 33 00:01:31,170 --> 00:01:33,230 And we'll just walk through it for a moment. 34 00:01:33,230 --> 00:01:36,300 Where he said at different ages, at infancy, early 35 00:01:36,300 --> 00:01:39,990 childhood, through school, adolescence, young adulthood, 36 00:01:39,990 --> 00:01:42,640 people are dealing with different kinds of issues and 37 00:01:42,640 --> 00:01:46,010 different developmental tasks in front of them. 38 00:01:46,010 --> 00:01:47,800 Your life is a constant development. 39 00:01:47,800 --> 00:01:50,870 Not maybe as dramatic as infancy where we saw last time 40 00:01:50,870 --> 00:01:53,400 that children really see the world differently. 41 00:01:53,400 --> 00:01:55,100 But there's different challenges in front 42 00:01:55,100 --> 00:01:57,690 of you at all ages. 43 00:01:57,690 --> 00:01:59,610 At infancy, you're deciding who can you 44 00:01:59,610 --> 00:02:00,960 trust, who can you love. 45 00:02:00,960 --> 00:02:03,520 Is it a good world? 46 00:02:03,520 --> 00:02:08,860 And then the drama of potty training, independence. 47 00:02:08,860 --> 00:02:12,510 How much are you becoming a free agent in the world? 48 00:02:12,510 --> 00:02:14,510 Early school, where you start to interact with other 49 00:02:14,510 --> 00:02:17,500 children, and play, and make friendships, and think about 50 00:02:17,500 --> 00:02:19,910 social groups. 51 00:02:19,910 --> 00:02:22,870 Later in schools, you're becoming more advanced in 52 00:02:22,870 --> 00:02:25,460 terms of what you're learning in school and more complex in 53 00:02:25,460 --> 00:02:27,480 terms of the social networks that you're developing. 54 00:02:30,520 --> 00:02:34,070 We'll come back to this at the end, a period of high anxiety 55 00:02:34,070 --> 00:02:39,130 and drama of adolescents. 56 00:02:39,130 --> 00:02:42,880 Then there's something about young adulthood. 57 00:02:42,880 --> 00:02:45,750 You may have heard recently people are speculating that 58 00:02:45,750 --> 00:02:48,380 what used to be the beginning of young adulthood culturally, 59 00:02:48,380 --> 00:02:51,930 at least in the US, and maybe Europe, and industrialized 60 00:02:51,930 --> 00:02:54,350 parts of the world, that whereas the '20s used to be 61 00:02:54,350 --> 00:02:57,090 considered a decade of adulthood, there are now 62 00:02:57,090 --> 00:02:59,370 theories floating around or impressions floating around 63 00:02:59,370 --> 00:03:02,270 that '20s are the new adolescence. 64 00:03:02,270 --> 00:03:04,710 What are you guys think? 65 00:03:04,710 --> 00:03:06,860 Everybody says, oh my '20s, I'm going to discover this and 66 00:03:06,860 --> 00:03:07,550 discover that. 67 00:03:07,550 --> 00:03:10,390 But when I get to 30, that's when we're playing for keeps. 68 00:03:14,520 --> 00:03:15,550 Is it? 69 00:03:15,550 --> 00:03:18,435 Well, and part of it's because you live longer, on average. 70 00:03:18,435 --> 00:03:19,370 Or you count on living longer. 71 00:03:19,370 --> 00:03:21,110 And you do, on average, live longer. 72 00:03:21,110 --> 00:03:25,160 For a person who's counting on living to 90, which many of 73 00:03:25,160 --> 00:03:28,710 you are sort of, another decade of finding your way, 74 00:03:28,710 --> 00:03:31,430 your 20s, seems reasonable. 75 00:03:31,430 --> 00:03:34,040 In a world where people didn't live nearly as long, didn't 76 00:03:34,040 --> 00:03:37,490 have as many options, by the time you finished college-- 77 00:03:37,490 --> 00:03:39,510 or many people didn't go to college-- it's roll up your 78 00:03:39,510 --> 00:03:41,180 sleeves and get to adulthood. 79 00:03:41,180 --> 00:03:44,920 So there's all these sort of magazine discussions, are the 80 00:03:44,920 --> 00:03:50,130 20s the new teens in terms of whether people feel they have 81 00:03:50,130 --> 00:03:54,900 responsibilities they have to execute as a young adult. 82 00:03:54,900 --> 00:03:57,820 And this a little bit timed also, a little bit 83 00:03:57,820 --> 00:04:00,300 anachronistic, then having a family. 84 00:04:00,300 --> 00:04:02,620 Although, I think we're much more thinking about that's not 85 00:04:02,620 --> 00:04:06,350 necessarily the root for everybody at all. 86 00:04:06,350 --> 00:04:09,920 And then old age where you give other 87 00:04:09,920 --> 00:04:12,920 people lots of advice. 88 00:04:12,920 --> 00:04:15,600 So we're going to talk about brain development from infancy 89 00:04:15,600 --> 00:04:18,700 to young adulthood, cognitive stability 90 00:04:18,700 --> 00:04:20,079 and decline in adulthood. 91 00:04:20,079 --> 00:04:21,209 We've talked a little bit about that. 92 00:04:21,209 --> 00:04:22,750 We'll talk a bit more. 93 00:04:22,750 --> 00:04:25,100 Alterations in hemispheric specializations 94 00:04:25,100 --> 00:04:28,290 that come with aging. 95 00:04:28,290 --> 00:04:32,520 A bunch of remarkable results about exercise in the brain. 96 00:04:32,520 --> 00:04:35,300 All of us want as we get older, or just even when 97 00:04:35,300 --> 00:04:37,500 you're younger maybe, just a pill you pop and 98 00:04:37,500 --> 00:04:39,150 you're ready to go. 99 00:04:39,150 --> 00:04:40,290 That would be the best. 100 00:04:40,290 --> 00:04:43,120 It turns out there's remarkable evidence about what 101 00:04:43,120 --> 00:04:44,700 physical exercise does for the brain. 102 00:04:44,700 --> 00:04:46,010 I'll share that with you-- especially in regards to 103 00:04:46,010 --> 00:04:47,840 aging, but at all ages-- 104 00:04:47,840 --> 00:04:50,190 ideas about how as you get older, your social and 105 00:04:50,190 --> 00:04:52,900 emotional goals will tend to change, a little bit about 106 00:04:52,900 --> 00:04:55,630 rewards, and a little bit about back to adolescence and 107 00:04:55,630 --> 00:04:58,000 some thoughts about what's going on in the adolescent 108 00:04:58,000 --> 00:04:59,270 mind and brain. 109 00:04:59,270 --> 00:05:01,060 So we know if there's one thing about the brain that's 110 00:05:01,060 --> 00:05:04,490 stunning, and challenging to grasp, and empowers us to be 111 00:05:04,490 --> 00:05:05,790 humans, it's this complexity. 112 00:05:05,790 --> 00:05:08,650 There's a huge number of neurons, fantastic number of 113 00:05:08,650 --> 00:05:11,030 connections among the neurons. 114 00:05:11,030 --> 00:05:14,750 So there's just a phenomenal complexity that all starts 115 00:05:14,750 --> 00:05:16,470 with a single cell. 116 00:05:16,470 --> 00:05:18,720 And how does the brain become this 117 00:05:18,720 --> 00:05:21,100 dramatically complex organ? 118 00:05:21,100 --> 00:05:24,580 And how does it organize in the right way to let you be an 119 00:05:24,580 --> 00:05:27,260 effective learner, an effective partner in your 120 00:05:27,260 --> 00:05:29,410 family, and so on? 121 00:05:29,410 --> 00:05:32,120 So we start with the idea of neurogenesis, a magical word, 122 00:05:32,120 --> 00:05:34,450 the neurons being born. 123 00:05:34,450 --> 00:05:38,960 And they have to make this crawl, there's a huge path the 124 00:05:38,960 --> 00:05:40,920 size of a neuron from the ventricular surface, the 125 00:05:40,920 --> 00:05:44,110 ventricle, the fluid-filled space, to get to the place 126 00:05:44,110 --> 00:05:45,040 you're going to be in the brain. 127 00:05:45,040 --> 00:05:47,940 It's a huge adventure per neuron. 128 00:05:47,940 --> 00:05:51,640 Cells dividing there, the earliest neurons are existing 129 00:05:51,640 --> 00:05:53,520 by the second embryonic week. 130 00:05:53,520 --> 00:05:55,190 So that's when you began to produce your 131 00:05:55,190 --> 00:05:57,340 neurons in your brain. 132 00:05:57,340 --> 00:05:59,600 By the seventh embryonic week-- so you're just two 133 00:05:59,600 --> 00:06:00,820 months of pregnancy-- 134 00:06:00,820 --> 00:06:06,020 you're producing an estimated 500,000 neurons a minute. 135 00:06:06,020 --> 00:06:09,620 We said the neuron is kind of like a moderate computer. 136 00:06:09,620 --> 00:06:11,840 Except unlike iPhones, it can't keep track of where 137 00:06:11,840 --> 00:06:14,090 you're going all the time. 138 00:06:14,090 --> 00:06:16,510 We said it's a moderate computer. 139 00:06:16,510 --> 00:06:22,740 So 500,000 of those every minute, I mean, staggering. 140 00:06:22,740 --> 00:06:24,495 That it all works out is staggering. 141 00:06:27,580 --> 00:06:30,640 By the 18th week, you've mostly made all the neurons 142 00:06:30,640 --> 00:06:33,080 you're ever going to make for the rest of your life except 143 00:06:33,080 --> 00:06:34,490 in two brain regions. 144 00:06:34,490 --> 00:06:36,960 And there's been a big debate in the last decade about 145 00:06:36,960 --> 00:06:37,680 another brain region. 146 00:06:37,680 --> 00:06:38,910 I'll share those with you. 147 00:06:38,910 --> 00:06:41,290 But people have been taught for many, many, many years in 148 00:06:41,290 --> 00:06:44,090 medical school, and college, and graduate school, that all 149 00:06:44,090 --> 00:06:46,180 the neurons you get are by the 18th week. 150 00:06:46,180 --> 00:06:48,030 So hang on to them through healthy 151 00:06:48,030 --> 00:06:50,340 living and wise behavior. 152 00:06:50,340 --> 00:06:51,910 Because you have what you have, right? 153 00:06:51,910 --> 00:06:52,660 So don't lose them. 154 00:06:52,660 --> 00:06:54,210 But we'll talk about that you lose the vast 155 00:06:54,210 --> 00:06:56,430 majority of them anyway. 156 00:06:56,430 --> 00:06:59,460 I still recommend healthy living. 157 00:06:59,460 --> 00:07:01,890 Because you know, perhaps from other courses, that the brain 158 00:07:01,890 --> 00:07:03,600 does this wild thing. 159 00:07:03,600 --> 00:07:07,460 It excessively overproduces, by massive scales, the number 160 00:07:07,460 --> 00:07:10,370 of neurons and the connections among the neurons. 161 00:07:10,370 --> 00:07:15,560 And then through use, it gets rid of neurons and gets rid of 162 00:07:15,560 --> 00:07:16,740 connections among neurons. 163 00:07:16,740 --> 00:07:19,350 It's exactly the opposite way if you build a building. 164 00:07:19,350 --> 00:07:21,060 If you build a building, what do you do? 165 00:07:21,060 --> 00:07:23,820 You construct every bit of it you need, and you're done. 166 00:07:23,820 --> 00:07:26,480 Well you don't do is say, I need a two-story building. 167 00:07:26,480 --> 00:07:29,150 So I'm going to do a 40-story building or a 90-story 168 00:07:29,150 --> 00:07:31,310 building and then knock off the stories 169 00:07:31,310 --> 00:07:32,030 as they're not needed. 170 00:07:32,030 --> 00:07:33,180 You say, well, that's wild. 171 00:07:33,180 --> 00:07:34,620 Why would I do that? 172 00:07:34,620 --> 00:07:38,030 But the brain brilliantly makes many more neurons and 173 00:07:38,030 --> 00:07:42,080 many more connections on epic scales and then only uses the 174 00:07:42,080 --> 00:07:45,280 ones that seem to be useful for the 175 00:07:45,280 --> 00:07:48,020 functions of the brain. 176 00:07:48,020 --> 00:07:53,680 And so for that reason, the density of the neurons in the 177 00:07:53,680 --> 00:07:57,360 brain is much higher in a two-year-old than in you, 178 00:07:57,360 --> 00:08:01,470 where it was much higher when you were two than it is now. 179 00:08:01,470 --> 00:08:06,220 So in a two-year-old, they have 55% more gray matter 180 00:08:06,220 --> 00:08:08,780 density in the frontal lobe than an adult. 181 00:08:08,780 --> 00:08:10,690 Even at age five, even at age seven, 182 00:08:10,690 --> 00:08:13,380 they're 10% percent more. 183 00:08:13,380 --> 00:08:17,220 From a peak of around before birth, you're constantly 184 00:08:17,220 --> 00:08:20,300 shedding neurons and their connections and keeping the 185 00:08:20,300 --> 00:08:23,260 ones that seem to be effective somehow. 186 00:08:23,260 --> 00:08:26,450 Now, for many years people said, is there neurogenesis in 187 00:08:26,450 --> 00:08:27,050 the adult brain? 188 00:08:27,050 --> 00:08:29,070 Is everything you get before you're born and 189 00:08:29,070 --> 00:08:31,170 that's pretty much it? 190 00:08:31,170 --> 00:08:32,730 And there's many reasons to be interested in that. 191 00:08:32,730 --> 00:08:34,380 One is just how does the brain work? 192 00:08:34,380 --> 00:08:35,470 How do people work? 193 00:08:35,470 --> 00:08:37,950 The second is for diseases like Alzheimer's disease, 194 00:08:37,950 --> 00:08:39,880 Parkinson's disease, and other diseases. 195 00:08:39,880 --> 00:08:43,110 We would love to replace neurons that have died to help 196 00:08:43,110 --> 00:08:44,940 people do better. 197 00:08:44,940 --> 00:08:50,570 So can the brain make new neurons before birth? 198 00:08:50,570 --> 00:08:53,230 There's compelling evidence in animals, and some indirect 199 00:08:53,230 --> 00:08:57,840 evidence in people too, that neurogenesis does continue 200 00:08:57,840 --> 00:09:01,980 into adulthood in the olfactory bulb and in this 201 00:09:01,980 --> 00:09:03,752 particular part-- and I'll come back to this-- in the 202 00:09:03,752 --> 00:09:05,940 hippocampus, a small part of the hippocampus called the 203 00:09:05,940 --> 00:09:06,730 dentate gyrus. 204 00:09:06,730 --> 00:09:08,955 Everybody's in pretty much agreement on this for the 205 00:09:08,955 --> 00:09:10,590 moment, which is kind of interesting. 206 00:09:10,590 --> 00:09:14,780 Why those two areas amongst all the areas in the brain? 207 00:09:14,780 --> 00:09:17,640 What makes them different that they can produce neurons all 208 00:09:17,640 --> 00:09:20,140 throughout your life? 209 00:09:20,140 --> 00:09:22,370 And then about a decade ago, Elizabeth Gould at Princeton 210 00:09:22,370 --> 00:09:25,520 said, oh, when I do the right kind of experiment, I see new 211 00:09:25,520 --> 00:09:30,232 neurons in the prefrontal cortex of monkeys, and for 212 00:09:30,232 --> 00:09:31,320 human primates. 213 00:09:31,320 --> 00:09:34,250 That was a giant revolution. 214 00:09:34,250 --> 00:09:35,500 Because they said, wait a minute. 215 00:09:35,500 --> 00:09:39,500 Maybe if monkeys are doing it, people might be doing it, 216 00:09:39,500 --> 00:09:41,100 making neurons throughout their life. 217 00:09:41,100 --> 00:09:41,950 We just did know that. 218 00:09:41,950 --> 00:09:43,150 It's not so easy to measure. 219 00:09:43,150 --> 00:09:45,980 If you think about it, the kind of experiment to know for 220 00:09:45,980 --> 00:09:50,440 certain if a human is making a new neuron is not so easy. 221 00:09:50,440 --> 00:09:52,020 Because brain imaging is very far from the 222 00:09:52,020 --> 00:09:53,260 single neuron level. 223 00:09:53,260 --> 00:09:57,745 And even if we saw a neuron, how could we tell it's new? 224 00:09:57,745 --> 00:10:01,090 And then Pasko Rakic, a big developmental researcher at 225 00:10:01,090 --> 00:10:04,360 Yale said, that what she really saw was glia. 226 00:10:04,360 --> 00:10:07,300 The glia are the other cells in the brain, not the neurons. 227 00:10:07,300 --> 00:10:09,460 They support the neurons. 228 00:10:09,460 --> 00:10:13,240 Everybody agrees that you make glia all through your life. 229 00:10:13,240 --> 00:10:14,600 There's no debate about that. 230 00:10:14,600 --> 00:10:16,990 But glia are not the stuff of thoughts and feelings. 231 00:10:16,990 --> 00:10:18,390 Neurons are. 232 00:10:18,390 --> 00:10:21,470 So what do we understand about that whole story? 233 00:10:21,470 --> 00:10:23,870 Here is an unbelievable experiment, I think. 234 00:10:23,870 --> 00:10:25,040 It's really not an experiment. 235 00:10:25,040 --> 00:10:26,290 But it's a measurement. 236 00:10:29,550 --> 00:10:33,770 Published in 2006, it's one approach to asking, do adults 237 00:10:33,770 --> 00:10:35,570 make new neurons? 238 00:10:35,570 --> 00:10:38,900 So the nuclear bomb tests that occur during the Cold War sent 239 00:10:38,900 --> 00:10:43,090 a carbon-14 into the atmosphere from 1955 to 1963 240 00:10:43,090 --> 00:10:45,380 until there was an international test ban treaty. 241 00:10:45,380 --> 00:10:47,660 And then these decreased and stopped. 242 00:10:47,660 --> 00:10:50,350 But there was a lot of nuclear bomb testing in the 243 00:10:50,350 --> 00:10:52,410 late '50s and '60s. 244 00:10:52,410 --> 00:10:55,380 That released carbon-14 into the atmosphere. 245 00:10:55,380 --> 00:10:58,530 And that integrates with DNA and forms a date mark for the 246 00:10:58,530 --> 00:10:59,600 cell of a birth. 247 00:10:59,600 --> 00:11:02,850 So this is not an experiment we would want to do again, 248 00:11:02,850 --> 00:11:05,210 atmospheric nuclear testing, and having nuclear stuff 249 00:11:05,210 --> 00:11:07,810 floating around in the atmosphere. 250 00:11:07,810 --> 00:11:09,340 I'll tell you the bottom line, and I'll show you how they 251 00:11:09,340 --> 00:11:10,820 figured this out. 252 00:11:10,820 --> 00:11:13,370 What they figured out is looking at people who died a 253 00:11:13,370 --> 00:11:15,170 few years ago, that 254 00:11:15,170 --> 00:11:16,850 nonneuronal cells are generated. 255 00:11:16,850 --> 00:11:19,200 That was found before glial cells are made throughout your 256 00:11:19,200 --> 00:11:21,080 lifetime is the inference from the finding. 257 00:11:21,080 --> 00:11:24,580 But neurons are not generated in adult neocortex. 258 00:11:24,580 --> 00:11:29,140 The commentary in this article said, no new neurons for you. 259 00:11:29,140 --> 00:11:30,110 OK, that's not quite true. 260 00:11:30,110 --> 00:11:32,570 We know these two little areas in the brain do it but not in 261 00:11:32,570 --> 00:11:33,720 most of the brain. 262 00:11:33,720 --> 00:11:37,060 And they also looked at something called BrdU, 263 00:11:37,060 --> 00:11:39,070 B-R-D-U, which is another way to take a 264 00:11:39,070 --> 00:11:41,510 brain if you have it. 265 00:11:41,510 --> 00:11:43,700 It marks newly synthesized DNA. 266 00:11:43,700 --> 00:11:46,030 So if you have the brain directly to measure it, you 267 00:11:46,030 --> 00:11:48,530 have a couple of measures of newly synthesized DNA, which 268 00:11:48,530 --> 00:11:51,090 would be the marker of new neurons. 269 00:11:51,090 --> 00:11:52,670 So here's a fantastically interesting thing. 270 00:11:52,670 --> 00:11:55,080 They took people who were born in different times, took 271 00:11:55,080 --> 00:11:59,580 postmortem samples, and measured carbon-14 relative to 272 00:11:59,580 --> 00:12:00,400 what was expected-- 273 00:12:00,400 --> 00:12:03,430 there's a line here-- it was relative to what was expected 274 00:12:03,430 --> 00:12:05,400 by the amount of carbon in the atmosphere. 275 00:12:08,250 --> 00:12:09,580 And here's what they found. 276 00:12:09,580 --> 00:12:13,320 If they look for somebody born after 1963, they have, in 277 00:12:13,320 --> 00:12:16,820 their neurons, exactly the amount that you would expect 278 00:12:16,820 --> 00:12:22,350 if they made all their neurons around here and the decrease 279 00:12:22,350 --> 00:12:25,320 here didn't affect the neurons at all. 280 00:12:25,320 --> 00:12:28,920 The glia are here, which is kind of an average of here and 281 00:12:28,920 --> 00:12:29,800 the rest of life. 282 00:12:29,800 --> 00:12:33,610 So if you measure the average age of the glia, it was about 283 00:12:33,610 --> 00:12:35,800 the average age of the life of the person the carbon was 284 00:12:35,800 --> 00:12:38,870 being picked up in the DNA, because it's being made. 285 00:12:38,870 --> 00:12:40,400 It's being kept, and being made. 286 00:12:40,400 --> 00:12:44,700 But the neurons all looked like one value, the value that 287 00:12:44,700 --> 00:12:47,500 has to do with when you're born. 288 00:12:47,500 --> 00:12:50,980 So it's not changing the number of neurons that are 289 00:12:50,980 --> 00:12:52,770 showing the carbon-14. 290 00:12:52,770 --> 00:12:54,910 As if whatever you've got at birth, that's it. 291 00:12:54,910 --> 00:12:58,450 On the other hand, here is somebody born before 1963, 292 00:12:58,450 --> 00:13:02,130 having essentially zero carbon that's being showing up in 293 00:13:02,130 --> 00:13:05,340 their neuronal DNA, and having again the expected average 294 00:13:05,340 --> 00:13:08,150 glial DNA as if glia kept going. 295 00:13:08,150 --> 00:13:09,100 So this is fantastic. 296 00:13:09,100 --> 00:13:11,610 It's looking at the carbon-14 in the DNA of neurons and 297 00:13:11,610 --> 00:13:13,620 glial of people who have passed away. 298 00:13:13,620 --> 00:13:17,120 And saying the carbon-14 dating looks like neurons. 299 00:13:17,120 --> 00:13:18,500 You get them all before you're born. 300 00:13:18,500 --> 00:13:19,080 That's it. 301 00:13:19,080 --> 00:13:20,970 Glia, you keep making. 302 00:13:20,970 --> 00:13:23,830 And they can look at it more directly by looking at this 303 00:13:23,830 --> 00:13:27,260 thing that shows you recent DNA, again, showing you 304 00:13:27,260 --> 00:13:31,140 impressively that glia keep making new glia with new DNA 305 00:13:31,140 --> 00:13:33,170 but not new neurons. 306 00:13:33,170 --> 00:13:35,380 So the current conclusion in the field, as far as anybody 307 00:13:35,380 --> 00:13:38,860 can tell, is no new neurons for you except in your dentate 308 00:13:38,860 --> 00:13:42,780 gyrus and olfactory bulb. 309 00:13:42,780 --> 00:13:45,060 Now here's something fantastic though. 310 00:13:45,060 --> 00:13:46,540 It appears that exercise-- 311 00:13:46,540 --> 00:13:48,980 I'll just show you one example in animals and humans-- 312 00:13:48,980 --> 00:13:52,790 there's evidence that exercise will pump up the number of new 313 00:13:52,790 --> 00:13:55,060 neurons you make in the dentate gyrus of the 314 00:13:55,060 --> 00:13:56,330 hippocampus. 315 00:13:56,330 --> 00:13:57,290 And we know that the hippocampus is 316 00:13:57,290 --> 00:13:58,200 important for memory. 317 00:13:58,200 --> 00:14:00,850 So that's not a bad place to make new neurons. 318 00:14:00,850 --> 00:14:03,340 So you know that going to exercise will strengthen you 319 00:14:03,340 --> 00:14:04,270 in various ways. 320 00:14:04,270 --> 00:14:06,490 But you never realized, unless you follow this line of work, 321 00:14:06,490 --> 00:14:09,890 that when you exercise, you're enhancing the number of new 322 00:14:09,890 --> 00:14:13,180 neurons that you're producing in your dentate gyrus. 323 00:14:13,180 --> 00:14:16,700 So here's a couple ways people have approached this. 324 00:14:16,700 --> 00:14:18,905 So one way is to measure cerebral blood volume, how 325 00:14:18,905 --> 00:14:20,480 much blood is in the dentate. 326 00:14:20,480 --> 00:14:23,780 And I'm going to show you evidence that mice that are 327 00:14:23,780 --> 00:14:27,800 allowed to exercise push up the blood volume. 328 00:14:27,800 --> 00:14:29,860 And that seems to go with direct evidence of 329 00:14:29,860 --> 00:14:30,430 neurogenesis. 330 00:14:30,430 --> 00:14:31,890 Because you can do that in the animals. 331 00:14:31,890 --> 00:14:34,200 You can look up sacrificed animals. 332 00:14:34,200 --> 00:14:37,010 And then in humans, some indirect evidence that 333 00:14:37,010 --> 00:14:39,970 exercise is, again, pushing up the blood volume in the 334 00:14:39,970 --> 00:14:42,590 dentate and pushing up a little bit of memory abilities 335 00:14:42,590 --> 00:14:44,010 that go with the part of the brain. 336 00:14:44,010 --> 00:14:48,060 We can't go in and measure neurons in the humans. 337 00:14:48,060 --> 00:14:51,210 So here are mice who exercise or didn't exercise. 338 00:14:51,210 --> 00:14:52,980 They measured the blood volume. 339 00:14:52,980 --> 00:14:56,350 Here in red is the dentate part of the hippocampus. 340 00:14:56,350 --> 00:15:00,060 You can see it's the hottest spot for blood volume. 341 00:15:00,060 --> 00:15:03,390 And it's the only part that responds to exercise. 342 00:15:03,390 --> 00:15:05,780 So they had some mice not get to exercise, 343 00:15:05,780 --> 00:15:07,780 some mice get to exercise. 344 00:15:07,780 --> 00:15:10,150 The blood volume increases within the hippocampus 345 00:15:10,150 --> 00:15:13,050 selectively in a small component of the hippocampus, 346 00:15:13,050 --> 00:15:14,040 the dentate gyrus. 347 00:15:14,040 --> 00:15:16,700 Exercise is pushing up the blood volume. 348 00:15:16,700 --> 00:15:18,470 Now that's not direct evidence about what's happening at the 349 00:15:18,470 --> 00:15:19,460 cellular level. 350 00:15:19,460 --> 00:15:22,840 But they can sacrifice these animals and show you that if 351 00:15:22,840 --> 00:15:26,080 you look at this binding that goes with new neurons, with 352 00:15:26,080 --> 00:15:29,750 new DNA, that's pushed up the exercise animals. 353 00:15:29,750 --> 00:15:31,160 Here's the statistics. 354 00:15:31,160 --> 00:15:32,980 Here's the picture. 355 00:15:32,980 --> 00:15:37,090 So in the animals, they can correlate directly. 356 00:15:37,090 --> 00:15:41,070 More blood volume and more new neurons going with more 357 00:15:41,070 --> 00:15:41,960 physical exercise. 358 00:15:41,960 --> 00:15:44,690 In humans, they can measure the blood volume. 359 00:15:44,690 --> 00:15:46,790 And so they had some people do more exercise, some people 360 00:15:46,790 --> 00:15:47,580 less exercise. 361 00:15:47,580 --> 00:15:49,870 Again, it was a dentate gyrus selectively. 362 00:15:49,870 --> 00:15:53,930 It showed an increase in blood volume in humans. 363 00:15:53,930 --> 00:15:55,280 And now they give them a memory test. 364 00:15:55,280 --> 00:15:56,900 And it's not overwhelming. 365 00:15:56,900 --> 00:15:59,570 But at least in some cases, the people who did exercising, 366 00:15:59,570 --> 00:16:02,230 who pushed up their blood volume, also pushed up a 367 00:16:02,230 --> 00:16:04,930 little bit their memory performance. 368 00:16:04,930 --> 00:16:07,840 So in humans it has to be more indirect, but all the data 369 00:16:07,840 --> 00:16:11,370 aligned with the idea that exercise is pushing up your 370 00:16:11,370 --> 00:16:14,200 own neuronal genesis, the creation of new neurons in one 371 00:16:14,200 --> 00:16:16,700 of the two regions everybody agrees we make new neurons, 372 00:16:16,700 --> 00:16:18,960 the dentate gyrus and the hippocampus. 373 00:16:21,920 --> 00:16:24,350 But cells have to go incredible distances at the 374 00:16:24,350 --> 00:16:25,250 cellular size. 375 00:16:25,250 --> 00:16:26,800 Neurons have to travel to the intended location. 376 00:16:26,800 --> 00:16:29,720 Migration occurs over many months including eight months 377 00:16:29,720 --> 00:16:30,650 postnatally. 378 00:16:30,650 --> 00:16:33,780 Here's this neuron following it's little path to where it's 379 00:16:33,780 --> 00:16:35,820 going to go. 380 00:16:35,820 --> 00:16:39,500 There's glial tracks following molecular cues as to their 381 00:16:39,500 --> 00:16:41,920 ultimate target location to get organized. 382 00:16:41,920 --> 00:16:44,380 Its initial destination and function are predetermined at 383 00:16:44,380 --> 00:16:45,190 the start of the migration. 384 00:16:45,190 --> 00:16:47,940 People can measure things in these that tell you where this 385 00:16:47,940 --> 00:16:48,520 is going to end up. 386 00:16:48,520 --> 00:16:51,240 It's programed in these cells. 387 00:16:51,240 --> 00:16:54,260 Unless there's something that blocks them, they know where 388 00:16:54,260 --> 00:16:55,480 they're going to go and make up different 389 00:16:55,480 --> 00:16:57,970 parts of the brain. 390 00:16:57,970 --> 00:17:00,830 And then they form synapses, the part where information is 391 00:17:00,830 --> 00:17:03,310 sent from one neuron to another. 392 00:17:03,310 --> 00:17:05,859 It occurs throughout the brain, but at different rates 393 00:17:05,859 --> 00:17:06,970 and different areas. 394 00:17:06,970 --> 00:17:10,500 So very early, you see it in spinal cord. 395 00:17:10,500 --> 00:17:13,420 Very late, you see it in higher cortical areas like 396 00:17:13,420 --> 00:17:15,079 prefrontal cortex. 397 00:17:15,079 --> 00:17:17,470 At the peak growth, there's an estimate-- these are all gross 398 00:17:17,470 --> 00:17:18,290 estimates-- 399 00:17:18,290 --> 00:17:23,280 that you may be forming 1.8 million synapses per second. 400 00:17:23,280 --> 00:17:26,910 It's stunning, 1.8 million synapses per second. 401 00:17:26,910 --> 00:17:29,510 And do you know how many molecules are in an average 402 00:17:29,510 --> 00:17:31,990 synapse by current estimations? 403 00:17:31,990 --> 00:17:32,970 1,000. 404 00:17:32,970 --> 00:17:35,860 There's 1,000 different molecules in a synapse for it 405 00:17:35,860 --> 00:17:37,300 to do it has to do. 406 00:17:37,300 --> 00:17:39,660 Multiply that times 1.8 million per second. 407 00:17:39,660 --> 00:17:43,210 It's spectacular biology. 408 00:17:43,210 --> 00:17:45,140 And then they keep getting more and more until two years. 409 00:17:45,140 --> 00:17:46,600 And then you start just losing them. 410 00:17:46,600 --> 00:17:48,770 By age 16, you'll have lost a lot of them. 411 00:17:48,770 --> 00:17:50,650 And so the people have this idea we mentioned before, 412 00:17:50,650 --> 00:17:51,640 pruning and selection. 413 00:17:51,640 --> 00:17:54,130 That we overgrow the number of neurons, the number of 414 00:17:54,130 --> 00:17:55,170 connections. 415 00:17:55,170 --> 00:17:57,640 What stays is activity dependence, or this use it or 416 00:17:57,640 --> 00:17:59,380 lose it neural Darwinism. 417 00:17:59,380 --> 00:18:00,560 Here's something amazing. 418 00:18:00,560 --> 00:18:04,770 There's an estimate that we lose 20 billion synapses per 419 00:18:04,770 --> 00:18:06,910 day through adolescence. 420 00:18:06,910 --> 00:18:09,060 And that's not a bad thing. 421 00:18:09,060 --> 00:18:10,920 That's not the worst behaving adolescents doing the worst 422 00:18:10,920 --> 00:18:12,020 things they can do. 423 00:18:12,020 --> 00:18:14,470 That's the brain getting rid of 424 00:18:14,470 --> 00:18:17,420 connections that aren't useful. 425 00:18:17,420 --> 00:18:19,090 It's an incredibly interesting way to 426 00:18:19,090 --> 00:18:20,670 construct a powerful brain. 427 00:18:20,670 --> 00:18:23,950 It's to get everybody to way overbuild. 428 00:18:23,950 --> 00:18:27,260 And then eliminate the ones that aren't powerfully useful. 429 00:18:30,260 --> 00:18:33,570 And another marker of development is myelination. 430 00:18:33,570 --> 00:18:36,720 That's the growth of the fatty sheath that surrounds the 431 00:18:36,720 --> 00:18:38,050 neurons that are extending distances. 432 00:18:38,050 --> 00:18:40,740 It insulates them and accelerates their signal. 433 00:18:40,740 --> 00:18:45,110 It looks like white matter in the postmortem brain. 434 00:18:45,110 --> 00:18:46,580 What happens through adolescence-- 435 00:18:46,580 --> 00:18:48,000 here's age four to 22-- 436 00:18:48,000 --> 00:18:55,260 is that white matter goes up, and gray matter goes down. 437 00:18:55,260 --> 00:18:57,990 So quite interesting, the total brain size from about 438 00:18:57,990 --> 00:19:01,100 age six to about 20-- young adulthood, most of you-- 439 00:19:01,100 --> 00:19:03,770 stays about the same, the total brain size. 440 00:19:03,770 --> 00:19:06,440 What you're doing is you're getting rid of gray matter. 441 00:19:06,440 --> 00:19:07,870 And you're enhancing white matter. 442 00:19:07,870 --> 00:19:09,800 You're getting rid of the neurons that are nonproductive 443 00:19:09,800 --> 00:19:11,850 and the synapses that are nonproductive. 444 00:19:11,850 --> 00:19:13,810 And you're increasing the strength with which different 445 00:19:13,810 --> 00:19:15,840 parts of the brain can communicate with one another 446 00:19:15,840 --> 00:19:18,610 through the white matter. 447 00:19:18,610 --> 00:19:21,610 And so here's the kinds of pictures of this growth. 448 00:19:21,610 --> 00:19:25,070 And some of the parts of the brain that mature latest by 449 00:19:25,070 --> 00:19:27,990 these kinds of measures of getting rid of the overgrowth, 450 00:19:27,990 --> 00:19:29,180 are in prefrontal cortex. 451 00:19:29,180 --> 00:19:30,430 And we've talked about that before. 452 00:19:34,150 --> 00:19:36,720 So many people are interested always in thinking about 453 00:19:36,720 --> 00:19:38,170 developmental issues and the biology of them. 454 00:19:38,170 --> 00:19:39,970 And here's a kind of a stunning finding. 455 00:19:39,970 --> 00:19:42,500 And we don't know exactly how it would relate to humans. 456 00:19:42,500 --> 00:19:43,900 But I thought it would be interesting to share with you 457 00:19:43,900 --> 00:19:45,920 and think about this just a little bit. 458 00:19:45,920 --> 00:19:48,920 So the title of the paper in science was "Good Memories of 459 00:19:48,920 --> 00:19:53,360 Bad Events in Infancy." So we know from before, and just 460 00:19:53,360 --> 00:19:56,040 common sense, that fear is important for the survival. 461 00:19:56,040 --> 00:19:57,940 So we start at the amygdala, which seems essential for 462 00:19:57,940 --> 00:20:00,540 learning what's to be feared. 463 00:20:00,540 --> 00:20:02,720 Because what's to be feared is what injures you, or worst 464 00:20:02,720 --> 00:20:05,100 case, could kill you. 465 00:20:05,100 --> 00:20:07,670 So the amygdala is essential for learned fear. 466 00:20:07,670 --> 00:20:10,110 And we know that one example, a fear condition that depends 467 00:20:10,110 --> 00:20:11,050 on the amygdala, would be a neutral 468 00:20:11,050 --> 00:20:13,220 stimulus like an odor-- 469 00:20:13,220 --> 00:20:16,650 odor that's not particularly good or bad, just an odor-- 470 00:20:16,650 --> 00:20:19,420 and then a shock that makes an aversive stimulus. 471 00:20:19,420 --> 00:20:21,640 So you pair them through conditioning, odor, shock, 472 00:20:21,640 --> 00:20:22,240 odor, shock. 473 00:20:22,240 --> 00:20:24,530 So the odor predicts the shock. 474 00:20:24,530 --> 00:20:29,640 Now, they looked at young rats and looked at attachments. 475 00:20:29,640 --> 00:20:31,310 And here's what they find kind of remarkably. 476 00:20:31,310 --> 00:20:35,250 Up to postnatal day nine for these rats, if they were 477 00:20:35,250 --> 00:20:38,920 exposed to the odors and the shocks, here's what they do. 478 00:20:38,920 --> 00:20:42,300 They know through pairings odor, shock, odor, shock, 479 00:20:42,300 --> 00:20:44,410 odor, shock, here comes the odor. 480 00:20:44,410 --> 00:20:45,660 Here comes the shock. 481 00:20:45,660 --> 00:20:47,700 They still approach the odors. 482 00:20:47,700 --> 00:20:48,710 That's what's in this graph. 483 00:20:48,710 --> 00:20:51,780 Up to nine days, the rats, the mice-- 484 00:20:51,780 --> 00:20:53,240 sorry-- 485 00:20:53,240 --> 00:20:57,410 are still approaching this odor even though it will lead 486 00:20:57,410 --> 00:20:58,950 to a shock. 487 00:20:58,950 --> 00:21:01,490 But on the 10th day, just one day later, 488 00:21:01,490 --> 00:21:02,710 it completely reverses. 489 00:21:02,710 --> 00:21:04,920 And they avoid the odors that predict the 490 00:21:04,920 --> 00:21:07,070 shock, a complete reversal. 491 00:21:07,070 --> 00:21:08,790 So they keep going to the odors with the shock. 492 00:21:08,790 --> 00:21:13,610 And on the 10th today, the pups stop going there. 493 00:21:13,610 --> 00:21:15,030 And what they also find is this. 494 00:21:15,030 --> 00:21:19,280 If they look at metabolic activity in the amygdala, for 495 00:21:19,280 --> 00:21:21,890 the nine-day olds, it's the same for the odor and the 496 00:21:21,890 --> 00:21:23,490 shock, where a neutral order. 497 00:21:23,490 --> 00:21:25,970 It's not selective to what's to be feared. 498 00:21:25,970 --> 00:21:29,270 And the 10-day old, here's a big response in the amygdala 499 00:21:29,270 --> 00:21:32,710 for the odor that predicts the shock, for the fearful 500 00:21:32,710 --> 00:21:34,710 learning, to know what's scary, and 501 00:21:34,710 --> 00:21:37,610 injurious and dangerous. 502 00:21:37,610 --> 00:21:39,090 So how do people think about this? 503 00:21:39,090 --> 00:21:42,100 Well, this is an animal experiment up to nine days. 504 00:21:42,100 --> 00:21:46,060 We can't really know how it relates to people. 505 00:21:46,060 --> 00:21:47,970 But the speculation was this. 506 00:21:47,970 --> 00:21:49,680 And maybe there's something to it on a 507 00:21:49,680 --> 00:21:50,990 different scale on people. 508 00:21:50,990 --> 00:21:57,210 Why would an animal approach something injurious, up to the 509 00:21:57,210 --> 00:21:59,330 amygdala seems to get more mature, and then 510 00:21:59,330 --> 00:22:00,560 avoid what's injurious. 511 00:22:00,560 --> 00:22:04,230 Why would that happen in such a predictable evolutionary 512 00:22:04,230 --> 00:22:06,700 determined way? 513 00:22:06,700 --> 00:22:08,780 And the hypothesis is this. 514 00:22:08,780 --> 00:22:14,260 That if you're a very helpless newborn, you have to go to 515 00:22:14,260 --> 00:22:16,630 things no matter what. 516 00:22:16,630 --> 00:22:18,930 Because you're so dependent on things in your 517 00:22:18,930 --> 00:22:21,240 environment to survive. 518 00:22:21,240 --> 00:22:24,190 But at some moment you mature enough that you 519 00:22:24,190 --> 00:22:25,390 say no thank you. 520 00:22:25,390 --> 00:22:27,660 If it's going to be shocking and painful, I'm 521 00:22:27,660 --> 00:22:28,870 going to avoid it. 522 00:22:28,870 --> 00:22:31,220 You become kind of independent in that sense, in 523 00:22:31,220 --> 00:22:32,730 the concrete sense. 524 00:22:32,730 --> 00:22:35,290 And so the author said, well, could it be helpful for 525 00:22:35,290 --> 00:22:39,400 newborns to know, no matter what, approach a caregiver, 526 00:22:39,400 --> 00:22:41,570 not respond to things that are negative, because you need the 527 00:22:41,570 --> 00:22:44,110 care, because you're so dependent. 528 00:22:44,110 --> 00:22:46,530 And now this is super speculatively. 529 00:22:46,530 --> 00:22:49,130 A thing that's been noted is that even in families where 530 00:22:49,130 --> 00:22:52,900 there's unfortunate tremendous abuse for a young child, the 531 00:22:52,900 --> 00:22:56,550 abuse victims so commonly remain powerful 532 00:22:56,550 --> 00:22:57,760 loyal to their parents. 533 00:22:57,760 --> 00:23:01,540 Is this kind of a mechanism that mixes up attachment and 534 00:23:01,540 --> 00:23:04,850 fear especially when you're young and can't separate them 535 00:23:04,850 --> 00:23:06,060 out so well? 536 00:23:06,060 --> 00:23:08,840 So it's a huge leap from the mice to the people. 537 00:23:08,840 --> 00:23:10,780 But it's a mechanism that we can understand might be 538 00:23:10,780 --> 00:23:13,920 involved in how attachment and fear can have unusual 539 00:23:13,920 --> 00:23:16,560 relationships with one another. 540 00:23:16,560 --> 00:23:18,510 All right. 541 00:23:18,510 --> 00:23:22,010 You can't avoid reading in the newspapers, or seeing on your 542 00:23:22,010 --> 00:23:25,410 computer screen, discussions about the deficit and older 543 00:23:25,410 --> 00:23:29,200 people like me demanding a lot of medical care that's paid 544 00:23:29,200 --> 00:23:33,710 for by the wages you're going to get in a couple years. 545 00:23:33,710 --> 00:23:34,960 I mean that's how I look at it. 546 00:23:38,020 --> 00:23:42,060 So you are entering a world, we're all entering a world, 547 00:23:42,060 --> 00:23:45,880 where the changing ages demography of our society is 548 00:23:45,880 --> 00:23:46,850 spectacular. 549 00:23:46,850 --> 00:23:48,730 Japan is ahead of us in this a little bit. 550 00:23:48,730 --> 00:23:50,260 The rest of the world is following. 551 00:23:50,260 --> 00:23:51,980 And China is going to be unbelievable when 552 00:23:51,980 --> 00:23:53,490 it happens on scale. 553 00:23:53,490 --> 00:23:56,000 But the United States right now, right now. 554 00:23:56,000 --> 00:23:57,150 And here's why. 555 00:23:57,150 --> 00:24:00,640 For most of human history, the average life expectancy was up 556 00:24:00,640 --> 00:24:01,310 to 20 years old. 557 00:24:01,310 --> 00:24:02,390 That's why you had to be an adult. 558 00:24:02,390 --> 00:24:04,550 Because at 20, who knows how much time I have. 559 00:24:04,550 --> 00:24:07,430 I better do my adult things. 560 00:24:07,430 --> 00:24:08,620 Some people lived for a long time. 561 00:24:08,620 --> 00:24:09,330 This is really interesting. 562 00:24:09,330 --> 00:24:12,390 It wasn't that everybody perished by 30. 563 00:24:12,390 --> 00:24:15,690 Some people lived to 60, 70, 80, 90. 564 00:24:15,690 --> 00:24:18,970 But many people fell ill to many diseases that are now 565 00:24:18,970 --> 00:24:20,670 readily cured. 566 00:24:20,670 --> 00:24:22,704 So the average age was 20. 567 00:24:22,704 --> 00:24:26,680 In the 1800s, it became the '30s, just a couple hundred 568 00:24:26,680 --> 00:24:28,720 years ago in all of human history. 569 00:24:28,720 --> 00:24:33,980 By 2000, the average person in the US lived until 77. 570 00:24:33,980 --> 00:24:36,670 By 2010, 78. 571 00:24:36,670 --> 00:24:40,170 So we're having a spectacular growth in the proportion of 572 00:24:40,170 --> 00:24:43,580 humans in our society who are living a long, long time, 573 00:24:43,580 --> 00:24:45,740 which is a wonderful thing. 574 00:24:45,740 --> 00:24:48,190 But it's radically changing the world we live in and the 575 00:24:48,190 --> 00:24:50,520 world for those people who are older as well. 576 00:24:50,520 --> 00:24:54,340 So, for example, 100-year-old people, there's 50,000 of them 577 00:24:54,340 --> 00:24:57,770 in the US, which is triple what there was a time ago. 578 00:24:57,770 --> 00:25:00,400 And it's expected to be a million people in the US who 579 00:25:00,400 --> 00:25:03,980 are 100 years and older by 2050, which is in your 580 00:25:03,980 --> 00:25:07,680 lifetime, a million people in the US alone 581 00:25:07,680 --> 00:25:10,800 will be 100 or older. 582 00:25:10,800 --> 00:25:15,100 And maybe 50% of girls born in 2000 will live for a century. 583 00:25:15,100 --> 00:25:19,400 Spectacular changes are occurring right this moment. 584 00:25:19,400 --> 00:25:23,680 The baby boom generation, huge numbers of us are approaching 585 00:25:23,680 --> 00:25:26,170 retirement and the kind of medical support that gets 586 00:25:26,170 --> 00:25:30,980 heavier when you get older on average, huge numbers of us. 587 00:25:30,980 --> 00:25:31,700 How's it changing? 588 00:25:31,700 --> 00:25:34,070 One way it's changing is that families often have-- and you 589 00:25:34,070 --> 00:25:36,555 might hear this-- an issue of families feeling that they're 590 00:25:36,555 --> 00:25:38,030 a sandwich generation. 591 00:25:38,030 --> 00:25:40,360 They're taking care of their children and the elderly. 592 00:25:40,360 --> 00:25:43,820 And you can bet if you have parents who are living to 120, 593 00:25:43,820 --> 00:25:46,600 you're doing that. 594 00:25:46,600 --> 00:25:49,490 Giant effects on education, pension, work, financial 595 00:25:49,490 --> 00:25:52,140 markets, I mean these are epic societal effects. 596 00:25:52,140 --> 00:25:54,450 So you're hearing the discussion now about how the 597 00:25:54,450 --> 00:25:56,860 US is going to deal with this. 598 00:25:56,860 --> 00:25:58,920 So there used to be kind of an old model. 599 00:25:58,920 --> 00:26:00,010 And even this is not that old. 600 00:26:00,010 --> 00:26:03,030 This is from the mid-1950s. 601 00:26:03,030 --> 00:26:06,900 Your job was to go to college, have a career, have a mate, 602 00:26:06,900 --> 00:26:09,110 take care of a kid, retire at 65, and put your 603 00:26:09,110 --> 00:26:10,560 feet up on the desk. 604 00:26:10,560 --> 00:26:12,900 But all of a sudden, if everybody's living-- 605 00:26:12,900 --> 00:26:15,030 not everybody, but huge numbers of people are living-- 606 00:26:15,030 --> 00:26:19,800 until 70, 80, 90, 100, many in pretty good health-- not 607 00:26:19,800 --> 00:26:22,220 everybody we wish for-- but many in pretty good health, 608 00:26:22,220 --> 00:26:24,230 that's a fantastically different thing. 609 00:26:24,230 --> 00:26:26,500 65 is no longer the retirement moment, and you're 610 00:26:26,500 --> 00:26:27,500 glad you made it. 611 00:26:27,500 --> 00:26:31,440 65 is something like the halfway point of your 612 00:26:31,440 --> 00:26:34,220 potential work life. 613 00:26:34,220 --> 00:26:38,070 20 to 60, 60 to 100, something like this. 614 00:26:38,070 --> 00:26:39,560 It's an unbelievable change. 615 00:26:39,560 --> 00:26:42,450 You cannot overestimate how it's changing the world around 616 00:26:42,450 --> 00:26:45,030 you, and how it will affect the economics and the politics 617 00:26:45,030 --> 00:26:49,230 of the world that the rest of us will be in for many years. 618 00:26:49,230 --> 00:26:52,070 There's about 10% of the population over 65 now. 619 00:26:52,070 --> 00:26:56,100 In 20 years, one out of every four people will be over 65 by 620 00:26:56,100 --> 00:26:57,850 current estimates. 621 00:26:57,850 --> 00:27:01,580 So we're going to elect whatever president we want. 622 00:27:01,580 --> 00:27:03,700 And older people go vote a lot more than younger people. 623 00:27:03,700 --> 00:27:04,440 You can change that. 624 00:27:04,440 --> 00:27:06,730 But that's how it is. 625 00:27:06,730 --> 00:27:10,310 So let's talk about adult development. 626 00:27:10,310 --> 00:27:13,090 I can tell you that if you compare adult development, 627 00:27:13,090 --> 00:27:15,600 very little is understood from 20 to 80. 628 00:27:15,600 --> 00:27:17,970 Almost all the research is taking something like college 629 00:27:17,970 --> 00:27:20,270 students, and something like 80-year-olds, 630 00:27:20,270 --> 00:27:21,030 and comparing them. 631 00:27:21,030 --> 00:27:24,810 So pretty much minimal information is available about 632 00:27:24,810 --> 00:27:26,190 everything between 20 and 80. 633 00:27:26,190 --> 00:27:28,430 But we'll look at what we can. 634 00:27:28,430 --> 00:27:30,430 And one of the things we'll talk about for a moment is the 635 00:27:30,430 --> 00:27:32,220 two kinds of studies we could look at for development. 636 00:27:32,220 --> 00:27:33,120 This could be about infants. 637 00:27:33,120 --> 00:27:35,780 But we're going to talk about adults. 638 00:27:35,780 --> 00:27:37,810 Cross-sectional versus longitudinal, so 639 00:27:37,810 --> 00:27:40,620 cross-sectional is I look at you as 20-year-olds. 640 00:27:40,620 --> 00:27:42,925 I look at some 80-year-olds in the Boston community and 641 00:27:42,925 --> 00:27:44,760 compare them. 642 00:27:44,760 --> 00:27:47,340 That's very different than looking at you at 20 and 643 00:27:47,340 --> 00:27:49,260 seeing you at 80. 644 00:27:49,260 --> 00:27:50,790 Because that's much more controlled. 645 00:27:50,790 --> 00:27:53,310 That's you with everything that's special and particular 646 00:27:53,310 --> 00:27:55,960 about you at 20 and 80. 647 00:27:55,960 --> 00:27:58,230 When you go get people who are 20-year-olds from one place 648 00:27:58,230 --> 00:28:02,100 and 80-year-olds from another, a cross-sectional , study, 649 00:28:02,100 --> 00:28:05,840 that's going to have all the differences that 650 00:28:05,840 --> 00:28:07,850 go with those cohorts. 651 00:28:07,850 --> 00:28:11,160 So what do we see in these kinds of things? 652 00:28:14,700 --> 00:28:16,300 So here's some measures. 653 00:28:16,300 --> 00:28:17,340 You've seen this kind of stuff before. 654 00:28:17,340 --> 00:28:19,085 For things like working memory, speed of processing, 655 00:28:19,085 --> 00:28:20,380 and long-term memory. 656 00:28:20,380 --> 00:28:22,570 Here's people in their '20s, people in their '80s, a ski 657 00:28:22,570 --> 00:28:26,250 scope of decline. 658 00:28:26,250 --> 00:28:28,420 Here's things like knowledge of vocabulary. 659 00:28:28,420 --> 00:28:31,000 And that stays more steady, so the crystallized fluid 660 00:28:31,000 --> 00:28:33,390 distinction you've already heard about before. 661 00:28:33,390 --> 00:28:36,470 So what are the strengths and limitations of cross-sectional 662 00:28:36,470 --> 00:28:38,560 versus longitudinal studies. 663 00:28:38,560 --> 00:28:41,200 So for cross-sectional studies, they're fast. 664 00:28:41,200 --> 00:28:43,760 If you're a scientist like a graduate student who has to do 665 00:28:43,760 --> 00:28:47,500 a Ph.D. thesis in a mere six or seven years, you can go to 666 00:28:47,500 --> 00:28:49,530 experiment with 20-year-olds and 80-year-olds and have a 667 00:28:49,530 --> 00:28:50,640 conclusion. 668 00:28:50,640 --> 00:28:52,930 If you're a graduate student who would have to test this 669 00:28:52,930 --> 00:28:56,960 class of 20 and come back to you in 60 years from now and 670 00:28:56,960 --> 00:29:00,540 see how you're doing, that's going to be slow progress. 671 00:29:00,540 --> 00:29:03,970 So that's why an overwhelming amount of evidence is 672 00:29:03,970 --> 00:29:05,970 cross-sectional. 673 00:29:05,970 --> 00:29:07,810 The problem with it is cohort effects. 674 00:29:07,810 --> 00:29:10,940 We discussed, for example, that IQ scores go up year by 675 00:29:10,940 --> 00:29:13,200 year throughout the world. 676 00:29:13,200 --> 00:29:15,290 So you're not really comparing equal things in terms of 677 00:29:15,290 --> 00:29:18,590 educational opportunities, nutrition, exposure to 678 00:29:18,590 --> 00:29:19,780 information on the internet. 679 00:29:19,780 --> 00:29:22,240 A 20-year-old and an 80-year-old have lived through 680 00:29:22,240 --> 00:29:24,390 different worlds. 681 00:29:24,390 --> 00:29:26,670 So it's all mixed up in the measurements. 682 00:29:26,670 --> 00:29:28,480 Not just age, it's different worlds that 683 00:29:28,480 --> 00:29:30,660 people have lived in. 684 00:29:30,660 --> 00:29:33,060 Longitudinal studies are painfully slow. 685 00:29:33,060 --> 00:29:34,920 They're more accurate, because you're looking at change 686 00:29:34,920 --> 00:29:35,570 within a person. 687 00:29:35,570 --> 00:29:38,570 You're holding all the world things constant. 688 00:29:38,570 --> 00:29:39,930 You have one other weird thing, which is you get 689 00:29:39,930 --> 00:29:40,910 practice effects. 690 00:29:40,910 --> 00:29:43,700 If you test somebody in the same test, if you're 60 years 691 00:29:43,700 --> 00:29:44,540 apart, you don't get much. 692 00:29:44,540 --> 00:29:46,570 But if it's maybe three or four years apart, you take a 693 00:29:46,570 --> 00:29:48,080 test twice, you get better at it. 694 00:29:48,080 --> 00:29:49,980 So that's a problem with longitudinal affects when you 695 00:29:49,980 --> 00:29:51,310 retest somebody. 696 00:29:51,310 --> 00:29:53,530 So there's been a few studies that have looked at relatively 697 00:29:53,530 --> 00:29:56,620 short-term longitudinal and cross-sectional data. 698 00:29:56,620 --> 00:30:00,840 And here's a ski slope on the values of fluid 699 00:30:00,840 --> 00:30:02,110 intelligence things. 700 00:30:02,110 --> 00:30:06,260 And it's just made a bit milder by a longitudinal 701 00:30:06,260 --> 00:30:07,840 design, but not dramatically different. 702 00:30:07,840 --> 00:30:10,500 So it's not the case of longitudinal studies. 703 00:30:10,500 --> 00:30:12,550 People used to think oh, these longitudinal studies are 704 00:30:12,550 --> 00:30:13,530 overestimating that. 705 00:30:13,530 --> 00:30:15,420 Especially if you're older, you like that thought. 706 00:30:15,420 --> 00:30:17,100 It's a messed up study approach. 707 00:30:17,100 --> 00:30:19,130 But unfortunately, cross-sectional ones just 708 00:30:19,130 --> 00:30:22,170 diminish the difference a little bit. 709 00:30:22,170 --> 00:30:25,170 So people have said, though, there's 710 00:30:25,170 --> 00:30:26,120 an interesting trade-off. 711 00:30:26,120 --> 00:30:27,860 What's the trade-off, then-- 712 00:30:27,860 --> 00:30:29,490 I'll ask you for a moment-- 713 00:30:29,490 --> 00:30:33,040 between most of you are like 18 to 22. 714 00:30:33,040 --> 00:30:36,340 I'll bracket it 17 to 25. 715 00:30:36,340 --> 00:30:38,220 Is that fair? 716 00:30:38,220 --> 00:30:42,250 What advantage do you have versus somebody in their 717 00:30:42,250 --> 00:30:44,980 mid-'50s like me? 718 00:30:44,980 --> 00:30:51,120 And what disadvantage do you have in some global sense? 719 00:30:51,120 --> 00:30:51,770 Oh. 720 00:30:51,770 --> 00:30:54,110 That was painful. 721 00:30:54,110 --> 00:30:56,750 The answer was you guys are physically able. 722 00:30:56,750 --> 00:30:57,190 All right. 723 00:30:57,190 --> 00:30:58,590 That would be true. 724 00:30:58,590 --> 00:31:00,340 There's not many Olympian sprinters who 725 00:31:00,340 --> 00:31:01,590 are in their mid-'50s. 726 00:31:03,570 --> 00:31:05,110 How about in terms of cognitive things? 727 00:31:08,650 --> 00:31:12,500 So we just said, for speed of mental processing, 728 00:31:12,500 --> 00:31:14,470 it's good to be 20. 729 00:31:14,470 --> 00:31:17,650 And then 30-year-olds are a little slower. 730 00:31:17,650 --> 00:31:18,720 40-year-olds, a little slower. 731 00:31:18,720 --> 00:31:22,540 50, 60, 70, every decade a little bit slower for speed of 732 00:31:22,540 --> 00:31:23,960 mental processing. 733 00:31:23,960 --> 00:31:25,800 But there's one thing that's an advantage 734 00:31:25,800 --> 00:31:27,900 with time for cognition. 735 00:31:27,900 --> 00:31:29,066 What's the advantage? 736 00:31:29,066 --> 00:31:30,404 AUDIENCE: [INAUDIBLE]. 737 00:31:30,404 --> 00:31:30,850 PROFESSOR: Sorry? 738 00:31:30,850 --> 00:31:31,836 AUDIENCE: Experience. 739 00:31:31,836 --> 00:31:32,960 PROFESSOR: Experience. 740 00:31:32,960 --> 00:31:33,320 Thank you. 741 00:31:33,320 --> 00:31:34,770 Oh yes. 742 00:31:34,770 --> 00:31:36,140 Yes. 743 00:31:36,140 --> 00:31:39,650 Over time, you learn stuff, especially stuff that you're 744 00:31:39,650 --> 00:31:40,630 exposed to a lot. 745 00:31:40,630 --> 00:31:44,120 So time is a trade-off within adulthood. 746 00:31:44,120 --> 00:31:46,700 You lose some speeded capacities. 747 00:31:46,700 --> 00:31:49,800 You gain some specific knowledge or experience. 748 00:31:49,800 --> 00:31:51,830 So they looked at studies like these, air traffic 749 00:31:51,830 --> 00:31:53,420 controllers in Canada. 750 00:31:53,420 --> 00:31:57,350 And this is very relevant. 751 00:31:57,350 --> 00:32:00,360 Especially now, air traffic controllers are in the news 752 00:32:00,360 --> 00:32:02,420 more than they want to be. 753 00:32:02,420 --> 00:32:02,790 You've seen them? 754 00:32:02,790 --> 00:32:04,030 Unfortunately, they're napping. 755 00:32:04,030 --> 00:32:05,390 They're playing movies, some of them. 756 00:32:05,390 --> 00:32:06,770 I'm sure it's a tiny minority. 757 00:32:06,770 --> 00:32:10,760 But it's worrisome if you're a member of the flying public. 758 00:32:10,760 --> 00:32:11,620 So here's another question. 759 00:32:11,620 --> 00:32:13,880 At what age should you tell somebody, well, I think we 760 00:32:13,880 --> 00:32:15,980 don't need you to be an air controller anymore, because 761 00:32:15,980 --> 00:32:19,680 you're not with it enough for us to feel safe. 762 00:32:19,680 --> 00:32:21,470 So people are probing this all the time. 763 00:32:24,150 --> 00:32:27,920 The average retirement age in the US is 55, in Canada, 65. 764 00:32:27,920 --> 00:32:29,860 Is one more correct than the other? 765 00:32:29,860 --> 00:32:31,870 And so here's what they found when they looked at air 766 00:32:31,870 --> 00:32:33,680 traffic controllers. 767 00:32:33,680 --> 00:32:35,950 Age influences processing speed but not task 768 00:32:35,950 --> 00:32:37,130 performance. 769 00:32:37,130 --> 00:32:39,470 So what we're thinking is older people aren't better. 770 00:32:39,470 --> 00:32:40,130 But they're not worse. 771 00:32:40,130 --> 00:32:42,880 Maybe there's a trade-off between speed and experience. 772 00:32:42,880 --> 00:32:45,930 And it kind of evens out until some age where it will no 773 00:32:45,930 --> 00:32:47,410 longer even out. 774 00:32:47,410 --> 00:32:51,420 118 pilots, 40 to 69, they took place in flight 775 00:32:51,420 --> 00:32:53,530 simulators and tested three times across three years. 776 00:32:53,530 --> 00:32:55,910 It's a longitudinal design and a flight simulator. 777 00:32:55,910 --> 00:32:59,720 The older pilots were worse the first time they did it. 778 00:32:59,720 --> 00:33:01,150 Now some time is passing. 779 00:33:01,150 --> 00:33:02,910 But then they outperformed the younger pilots in 780 00:33:02,910 --> 00:33:04,350 years two and three. 781 00:33:04,350 --> 00:33:06,310 That is, once they had some experience with the new 782 00:33:06,310 --> 00:33:09,000 situation, they could apply, presumably, their prior 783 00:33:09,000 --> 00:33:10,510 experience. 784 00:33:10,510 --> 00:33:12,520 But the very first time they did it when they have to use 785 00:33:12,520 --> 00:33:14,320 their fluid intelligence to figure out what's going on, 786 00:33:14,320 --> 00:33:15,250 they were worse. 787 00:33:15,250 --> 00:33:19,200 So you can see some trade-offs between raw processing, speed, 788 00:33:19,200 --> 00:33:22,700 and flexibility that goes with the young adulthood and some 789 00:33:22,700 --> 00:33:23,970 degree of knowledge and expertise 790 00:33:23,970 --> 00:33:24,990 that's gained over time. 791 00:33:24,990 --> 00:33:28,180 There's trade-offs on these things. 792 00:33:28,180 --> 00:33:30,180 How about in memory, declarative memory that we 793 00:33:30,180 --> 00:33:31,910 talked about, every day memory. 794 00:33:31,910 --> 00:33:32,570 I'll show you in a moment. 795 00:33:32,570 --> 00:33:35,720 There's mild, steady decline in healthy aging severe in 796 00:33:35,720 --> 00:33:36,900 Alzheimer's. 797 00:33:36,900 --> 00:33:38,670 Implicit memory, we talked about that. 798 00:33:38,670 --> 00:33:40,690 It can be more steady across ages. 799 00:33:40,690 --> 00:33:44,340 But let me focus on explicit memory, declarative memory. 800 00:33:44,340 --> 00:33:46,990 We're going to figure out why the projector is washing these 801 00:33:46,990 --> 00:33:47,710 things out so much. 802 00:33:47,710 --> 00:33:49,850 But here's a slide that you don't have to see 803 00:33:49,850 --> 00:33:51,010 very much to know. 804 00:33:51,010 --> 00:33:54,650 Long-term memory performance is going down quite sharply 805 00:33:54,650 --> 00:33:57,640 year by year as you get older. 806 00:33:57,640 --> 00:33:59,970 But here's something that was a huge surprise from brain 807 00:33:59,970 --> 00:34:01,200 imaging, a huge surprise. 808 00:34:01,200 --> 00:34:02,940 And the thing that if you didn't have brain imaging, you 809 00:34:02,940 --> 00:34:05,650 wouldn't even conceive that it could have existed. 810 00:34:05,650 --> 00:34:08,310 So many studies have done brain imaging as people 811 00:34:08,310 --> 00:34:10,960 perform various kinds of tasks, memory tasks in this 812 00:34:10,960 --> 00:34:13,580 case, with young adults and older adults. 813 00:34:13,580 --> 00:34:13,710 And 814 00:34:13,710 --> 00:34:17,500 what they found, unexpectedly, was this. 815 00:34:17,500 --> 00:34:22,710 Young adults would typically activate one side of the 816 00:34:22,710 --> 00:34:25,090 prefrontal cortex typically in regards to whether it was 817 00:34:25,090 --> 00:34:26,380 verbal or spatial. 818 00:34:26,380 --> 00:34:29,460 So here's young adults mostly on one side, mostly on one 819 00:34:29,460 --> 00:34:34,580 side, mostly on one side, mostly on one side. 820 00:34:34,580 --> 00:34:37,940 Healthy older adults in good health characteristically 821 00:34:37,940 --> 00:34:41,630 turned on both sides of the brain as they were performing 822 00:34:41,630 --> 00:34:44,150 these memory tasks. 823 00:34:44,150 --> 00:34:45,870 So you wouldn't have known that if you didn't have 824 00:34:45,870 --> 00:34:49,260 imaging, because who could have thought about that? 825 00:34:49,260 --> 00:34:52,620 So then there was a little bit of a debate in the field with 826 00:34:52,620 --> 00:34:55,679 the fact that adults were turning on both sides of their 827 00:34:55,679 --> 00:34:58,200 hemispheres whereas adults were just picking one 828 00:34:58,200 --> 00:34:59,220 or just using one. 829 00:34:59,220 --> 00:35:01,450 Was that a good thing or a bad thing? 830 00:35:01,450 --> 00:35:03,960 So people said, well, it's a bad thing. 831 00:35:03,960 --> 00:35:05,860 Because maybe as you get older, you lose your 832 00:35:05,860 --> 00:35:09,550 specializations, and you're using the wrong stuff. 833 00:35:09,550 --> 00:35:10,820 It's as if I need my physics book. 834 00:35:10,820 --> 00:35:12,600 And I'm going to grab my chemistry book. 835 00:35:12,600 --> 00:35:14,930 Well, just grab your physics book. 836 00:35:14,930 --> 00:35:16,330 Just grab the right thing. 837 00:35:16,330 --> 00:35:18,770 Why are you getting other stuff that's not relevant that 838 00:35:18,770 --> 00:35:20,440 could mess you up and slow you down? 839 00:35:20,440 --> 00:35:22,360 So some people said, you're sort of losing the 840 00:35:22,360 --> 00:35:24,460 specializations of peak young adulthood. 841 00:35:24,460 --> 00:35:28,110 You're leaking brain activity in the wrong places. 842 00:35:28,110 --> 00:35:31,070 It's yet another sad sign of getting older. 843 00:35:31,070 --> 00:35:32,390 Here's an alternative one. 844 00:35:32,390 --> 00:35:33,100 Well, you get older. 845 00:35:33,100 --> 00:35:35,220 But maybe you get some compensatory mechanisms. 846 00:35:35,220 --> 00:35:38,070 You realize at some level in your brain that you can't do 847 00:35:38,070 --> 00:35:39,900 what you could when you were 20. 848 00:35:39,900 --> 00:35:43,040 And you make up for that by somehow using two sides of 849 00:35:43,040 --> 00:35:44,790 your brain instead of one. 850 00:35:44,790 --> 00:35:46,300 So that would be a good thing. 851 00:35:46,300 --> 00:35:49,690 So how would you decide that? 852 00:35:49,690 --> 00:35:52,270 How would you decide whether using the two sides of your 853 00:35:52,270 --> 00:35:56,400 brain when you're an older adult is a helpful thing, part 854 00:35:56,400 --> 00:35:59,920 of the solution to keeping your cognition going, or is it 855 00:35:59,920 --> 00:36:03,720 part of the problem of losing long-term memory abilities as 856 00:36:03,720 --> 00:36:04,790 you get older while they're declining. 857 00:36:04,790 --> 00:36:06,640 How would you decide that? 858 00:36:06,640 --> 00:36:08,540 There's kind of an easy answer. 859 00:36:08,540 --> 00:36:08,980 AUDIENCE: [INAUDIBLE]. 860 00:36:08,980 --> 00:36:09,820 PROFESSOR: Sorry. 861 00:36:09,820 --> 00:36:11,380 AUDIENCE: [INAUDIBLE]. 862 00:36:11,380 --> 00:36:12,250 PROFESSOR: You what? 863 00:36:12,250 --> 00:36:14,300 AUDIENCE: Like, split their brains. 864 00:36:14,300 --> 00:36:16,670 PROFESSOR: Yes. 865 00:36:16,670 --> 00:36:18,490 It's a suggestion we should take older people, split their 866 00:36:18,490 --> 00:36:21,620 brains, and see how they're doing. 867 00:36:21,620 --> 00:36:24,300 Well, older people, their long-term 868 00:36:24,300 --> 00:36:26,090 memory is not that bad. 869 00:36:26,090 --> 00:36:27,610 So here was the approach. 870 00:36:27,610 --> 00:36:28,470 It seems reasonable. 871 00:36:28,470 --> 00:36:31,000 They say amongst older people, some people do better and 872 00:36:31,000 --> 00:36:33,240 worse in terms of the memory. 873 00:36:33,240 --> 00:36:37,070 Does better memory go with using two sides or one side? 874 00:36:37,070 --> 00:36:39,660 And what was found, and here's one example. 875 00:36:39,660 --> 00:36:42,330 Here's young people using one side of their frontal cortex 876 00:36:42,330 --> 00:36:43,930 as they perform a memory task. 877 00:36:43,930 --> 00:36:46,750 Here's older people whose memory was not so good. 878 00:36:46,750 --> 00:36:48,510 Here's older people whose memory was good. 879 00:36:48,510 --> 00:36:50,450 And here's a similar finding. 880 00:36:50,450 --> 00:36:54,620 So the suggestion was that older people who used both 881 00:36:54,620 --> 00:36:56,930 frontal cortices were actually doing better. 882 00:36:56,930 --> 00:36:59,750 They were having less of an effective age on cognition. 883 00:36:59,750 --> 00:37:02,710 So the answer seems to be, it's a good thing. 884 00:37:02,710 --> 00:37:05,120 And if you're older, you somehow compensate for some of 885 00:37:05,120 --> 00:37:09,030 the decrease in long-term ability by applying more 886 00:37:09,030 --> 00:37:10,690 neural systems to support your performance. 887 00:37:16,170 --> 00:37:17,580 Older adults are really interested in this. 888 00:37:17,580 --> 00:37:18,190 You are not. 889 00:37:18,190 --> 00:37:20,270 In about 30 years, you might be. 890 00:37:20,270 --> 00:37:22,410 But older adults are really interested in what can I do to 891 00:37:22,410 --> 00:37:23,340 keep myself going? 892 00:37:23,340 --> 00:37:27,650 Because I'm going to live to be 80, 90, or 100 with just a 893 00:37:27,650 --> 00:37:28,970 little bit of luck. 894 00:37:28,970 --> 00:37:32,160 How can I keep my quality of life high in terms of 895 00:37:32,160 --> 00:37:34,220 cognition and mental abilities? 896 00:37:34,220 --> 00:37:37,160 So one thing that people have found is that, on average, 897 00:37:37,160 --> 00:37:41,320 higher education is correlated with-- and there's many 898 00:37:41,320 --> 00:37:42,950 interpretations of this-- 899 00:37:42,950 --> 00:37:45,750 better cognitive abilities and less likelihood of getting 900 00:37:45,750 --> 00:37:47,450 Alzheimer's, or getting Alzheimer's, if you're going 901 00:37:47,450 --> 00:37:50,860 to get it, at an older age. 902 00:37:50,860 --> 00:37:52,940 So that's kind of interesting. 903 00:37:52,940 --> 00:37:54,150 It's good to go to college. 904 00:37:54,150 --> 00:37:55,910 It's good to keep being educated in some sense. 905 00:37:55,910 --> 00:37:57,340 It doesn't have to be formal. 906 00:37:57,340 --> 00:38:00,450 But formal education correlates with that. 907 00:38:00,450 --> 00:38:01,480 Now here was a surprise. 908 00:38:01,480 --> 00:38:02,360 And now you tell me what it is. 909 00:38:02,360 --> 00:38:03,990 So how would that work? 910 00:38:03,990 --> 00:38:05,860 How would sitting there and listening to me really 911 00:38:05,860 --> 00:38:09,850 carefully right now give you an extra decade of cognitive 912 00:38:09,850 --> 00:38:12,581 ability when you're 80? 913 00:38:12,581 --> 00:38:14,500 All right, now I've got your attention. 914 00:38:14,500 --> 00:38:16,470 How would that work biologically? 915 00:38:16,470 --> 00:38:18,850 Is education kind of going in your brain and saying, we're 916 00:38:18,850 --> 00:38:19,720 knocking all these things in. 917 00:38:19,720 --> 00:38:20,490 And we're keeping them here. 918 00:38:20,490 --> 00:38:22,230 And we're not going to let you have any injury when 919 00:38:22,230 --> 00:38:23,000 you're 40 or 50. 920 00:38:23,000 --> 00:38:24,560 How does that work? 921 00:38:24,560 --> 00:38:26,480 So I'm going to tell you one more piece of information, 922 00:38:26,480 --> 00:38:26,950 which is this. 923 00:38:26,950 --> 00:38:28,930 And you tell me what you think. 924 00:38:28,930 --> 00:38:31,680 So the other thing that we know is there's evidence that 925 00:38:31,680 --> 00:38:37,020 once you get the diagnosis of Alzheimer's disease, then the 926 00:38:37,020 --> 00:38:39,385 more educated you are, the faster you decline. 927 00:38:44,690 --> 00:38:46,430 And I don't think the story is all done yet. 928 00:38:46,430 --> 00:38:47,730 Because people are complicated. 929 00:38:47,730 --> 00:38:49,470 But this is the current evidence. 930 00:38:49,470 --> 00:38:52,580 So how do you interpret that? 931 00:38:52,580 --> 00:38:53,700 So here's the interpretation. 932 00:38:53,700 --> 00:38:56,650 The interpretation is more education gives you more 933 00:38:56,650 --> 00:38:59,190 mental tools, what people will call cognitive reserve. 934 00:38:59,190 --> 00:39:01,840 You have more things going for you like maybe the ability to 935 00:39:01,840 --> 00:39:04,310 use two hemispheres. 936 00:39:04,310 --> 00:39:08,110 That will protect you as something like some brain 937 00:39:08,110 --> 00:39:10,780 injury happens over time, like an Alzheimer's disease, or 938 00:39:10,780 --> 00:39:13,770 other causes of slowed or diminished 939 00:39:13,770 --> 00:39:14,770 cognition in old age. 940 00:39:14,770 --> 00:39:15,600 That will help you. 941 00:39:15,600 --> 00:39:18,170 You have more tools with which to keep operating 942 00:39:18,170 --> 00:39:19,770 successfully. 943 00:39:19,770 --> 00:39:22,340 But once Alzheimer's disease become severe enough in the 944 00:39:22,340 --> 00:39:25,070 brain that those tools are no longer available to you, then 945 00:39:25,070 --> 00:39:27,680 the more educated you are, the more you plummet. 946 00:39:27,680 --> 00:39:30,680 Because everything's done. 947 00:39:30,680 --> 00:39:32,250 So we now know something-- and I'll just say 948 00:39:32,250 --> 00:39:32,680 a word about this-- 949 00:39:32,680 --> 00:39:34,630 Alzheimer's disease-- and this is compelling 950 00:39:34,630 --> 00:39:35,530 evidence for this-- 951 00:39:35,530 --> 00:39:40,540 starts in your brain about 15 years 952 00:39:40,540 --> 00:39:42,550 before you get the diagnosis. 953 00:39:42,550 --> 00:39:44,840 And it could be more than that. 954 00:39:44,840 --> 00:39:47,690 That's how far we can track it back by brain imaging. 955 00:39:47,690 --> 00:39:51,830 So if an adult is diagnosed with Alzheimer's at 70, 956 00:39:51,830 --> 00:39:57,330 somewhere around 55, something has started that will 957 00:39:57,330 --> 00:40:00,960 ultimately be injury enough to lead to dementia and 958 00:40:00,960 --> 00:40:02,610 Alzheimer's disease. 959 00:40:02,610 --> 00:40:05,520 And that's why there's such a big emphasis on early 960 00:40:05,520 --> 00:40:06,850 identification. 961 00:40:06,850 --> 00:40:08,540 Because it's very hard to treat a brain that's 962 00:40:08,540 --> 00:40:10,090 had a lot of injury. 963 00:40:10,090 --> 00:40:12,580 You want to catch the people at 55 or 60. 964 00:40:12,580 --> 00:40:15,540 So we also know that lifelong cognitively is good. 965 00:40:15,540 --> 00:40:17,490 Conscientious, we talked about that. 966 00:40:17,490 --> 00:40:19,155 And here, again, comes exercise. 967 00:40:22,630 --> 00:40:23,730 So they took a study. 968 00:40:23,730 --> 00:40:25,470 This is now a random assignment study, finally a 969 00:40:25,470 --> 00:40:29,760 full on experiment, where they took sedentary people, people 970 00:40:29,760 --> 00:40:31,880 who were not exercising over 60, and assigned them to two 971 00:40:31,880 --> 00:40:35,390 groups, an aerobic training group who did walking and 972 00:40:35,390 --> 00:40:37,085 swimming, so some really exercise, and non-aerobic 973 00:40:37,085 --> 00:40:39,090 group who did toning and stretching. 974 00:40:39,090 --> 00:40:40,750 So they thought they were special. 975 00:40:40,750 --> 00:40:41,600 They were active. 976 00:40:41,600 --> 00:40:44,040 But they weren't doing the aerobic exercise. 977 00:40:44,040 --> 00:40:46,640 And they didn't do it a phenomenal amount of time, an 978 00:40:46,640 --> 00:40:48,300 hour a day, a few times a week for months. 979 00:40:48,300 --> 00:40:51,400 It's not a brutal exercise schedule. 980 00:40:51,400 --> 00:40:52,570 What happens? 981 00:40:52,570 --> 00:40:54,250 It's kind of amazing what happened. 982 00:40:54,250 --> 00:40:56,760 These are healthy people but not very active. 983 00:40:56,760 --> 00:40:59,620 What's shown here in the red bars are the cognitive 984 00:40:59,620 --> 00:41:02,500 performances after the exercise of the 985 00:41:02,500 --> 00:41:03,260 healthy older people. 986 00:41:03,260 --> 00:41:05,980 And blue bars are the people who did the stretching and 987 00:41:05,980 --> 00:41:07,540 toning, not the aerobic exercise. 988 00:41:07,540 --> 00:41:10,730 So very substantial gains in cognitive abilities from a few 989 00:41:10,730 --> 00:41:13,220 months of moderate exercise. 990 00:41:13,220 --> 00:41:17,620 And in the brain, both by functional MRI and by 991 00:41:17,620 --> 00:41:21,410 structural MRI, in gray matter, and white matter, 992 00:41:21,410 --> 00:41:24,320 physically measurable changes in the brain for the group 993 00:41:24,320 --> 00:41:28,740 that did the aerobic exercise a couple times a week for a 994 00:41:28,740 --> 00:41:30,760 few months compared to the group that did 995 00:41:30,760 --> 00:41:34,000 the less active exercises. 996 00:41:34,000 --> 00:41:34,730 That's amazing. 997 00:41:34,730 --> 00:41:36,390 The brain changes. 998 00:41:36,390 --> 00:41:38,300 Cognition changes. 999 00:41:38,300 --> 00:41:40,720 Again, no pill you can pop. 1000 00:41:40,720 --> 00:41:43,790 And you're making new neurons in your dentate gyrus to boot. 1001 00:41:43,790 --> 00:41:46,530 So all of us want the easy out. 1002 00:41:46,530 --> 00:41:49,740 But exercise is the most compelling story for keeping 1003 00:41:49,740 --> 00:41:53,060 your brain optimized that we know. 1004 00:41:53,060 --> 00:41:54,150 Now here's a remarkable thing. 1005 00:41:54,150 --> 00:41:56,110 Exercise, we kind of get. 1006 00:41:56,110 --> 00:41:58,290 Actually, if you think about it, we don't know the 1007 00:41:58,290 --> 00:42:00,260 mechanism at all. 1008 00:42:00,260 --> 00:42:02,080 I mean, you're running around like this. 1009 00:42:02,080 --> 00:42:04,530 Now how is that pushing up your neurons in your brain? 1010 00:42:04,530 --> 00:42:06,770 But here's something very psychological 1011 00:42:06,770 --> 00:42:07,990 that's kind of stunning. 1012 00:42:07,990 --> 00:42:09,770 And at first, I almost didn't believe it when I read it. 1013 00:42:09,770 --> 00:42:10,825 But there's been a few other studies that 1014 00:42:10,825 --> 00:42:12,180 have supported this. 1015 00:42:12,180 --> 00:42:14,950 We often think, well, exercise is something real. 1016 00:42:14,950 --> 00:42:17,590 Attitudes, even in a psychology course, attitudes, 1017 00:42:17,590 --> 00:42:19,160 they're just attitudes. 1018 00:42:19,160 --> 00:42:20,180 So look at this. 1019 00:42:20,180 --> 00:42:21,930 And then you can think about this. 1020 00:42:21,930 --> 00:42:25,750 So they looked in a longitudinal study of over 400 1021 00:42:25,750 --> 00:42:27,480 in the Baltimore Longitudinal Study of Aging. 1022 00:42:27,480 --> 00:42:28,360 They started under 50. 1023 00:42:28,360 --> 00:42:29,930 But they kept going with them. 1024 00:42:29,930 --> 00:42:32,900 They gave them a questionnaire on attitudes about aging. 1025 00:42:32,900 --> 00:42:34,740 So they said, are older people, for example, more 1026 00:42:34,740 --> 00:42:36,470 absent-minded or less intelligent? 1027 00:42:36,470 --> 00:42:38,470 And some people say, oh my gosh. 1028 00:42:38,470 --> 00:42:40,040 Older people are very absent-minded. 1029 00:42:40,040 --> 00:42:41,710 They're very less intelligent. 1030 00:42:41,710 --> 00:42:43,170 Other people think it's just a milder think. 1031 00:42:43,170 --> 00:42:45,980 People vary in their estimates of how severe these changes 1032 00:42:45,980 --> 00:42:47,810 are in old age. 1033 00:42:47,810 --> 00:42:50,250 Then they measured something very concrete and real, the 1034 00:42:50,250 --> 00:42:54,210 number of cardiovascular events, like stroke or heart 1035 00:42:54,210 --> 00:42:58,050 attack, over the next 38 years. 1036 00:42:58,050 --> 00:42:59,710 So this is a real physical measurement. 1037 00:42:59,710 --> 00:43:00,980 This isn't an attitude. 1038 00:43:00,980 --> 00:43:03,170 How powerful is an attitude? 1039 00:43:03,170 --> 00:43:05,590 Well, it's kind of stunning, unbelievably 1040 00:43:05,590 --> 00:43:07,490 powerful in some ways. 1041 00:43:07,490 --> 00:43:08,710 We don't know if it's the attitude or something 1042 00:43:08,710 --> 00:43:09,680 correlated. 1043 00:43:09,680 --> 00:43:13,600 But here's the percent with strokes or heart attacks. 1044 00:43:13,600 --> 00:43:18,270 Here's the people who had negative age stereotypes. 1045 00:43:18,270 --> 00:43:21,890 And here's the people who had positive age stereotypes. 1046 00:43:21,890 --> 00:43:23,460 So one always has to be worried about the 1047 00:43:23,460 --> 00:43:25,060 chicken and egg issue. 1048 00:43:25,060 --> 00:43:26,840 Maybe if you had a lot of strokes and heart attacks, 1049 00:43:26,840 --> 00:43:28,980 you're not so optimistic about your old age. 1050 00:43:28,980 --> 00:43:31,300 But they were measuring these things at the beginning, they 1051 00:43:31,300 --> 00:43:32,170 were very similar. 1052 00:43:32,170 --> 00:43:33,300 So they weren't starting out with 1053 00:43:33,300 --> 00:43:34,600 different health problems. 1054 00:43:34,600 --> 00:43:38,180 So something about attitudes seems to chip in to the most 1055 00:43:38,180 --> 00:43:40,120 core aspects of physical health. 1056 00:43:40,120 --> 00:43:42,020 But none of us understand the mechanism. 1057 00:43:42,020 --> 00:43:42,360 Yes? 1058 00:43:42,360 --> 00:43:43,993 AUDIENCE: Wouldn't family history have a 1059 00:43:43,993 --> 00:43:45,610 lot to do with that? 1060 00:43:45,610 --> 00:43:46,970 PROFESSOR: So the question is how about family history? 1061 00:43:46,970 --> 00:43:48,180 It could be mixed into that. 1062 00:43:48,180 --> 00:43:48,930 AUDIENCE: [INTERPOSING VOICES]. 1063 00:43:48,930 --> 00:43:49,780 PROFESSOR: Yeah. 1064 00:43:49,780 --> 00:43:51,901 That's a very good. 1065 00:43:51,901 --> 00:43:54,400 Then it's not just attitudes, right? 1066 00:43:54,400 --> 00:43:55,810 Or it could be not attitudes it all. 1067 00:43:59,040 --> 00:44:01,020 And here's the concept. 1068 00:44:01,020 --> 00:44:03,980 That regardless of your age-- but age is one of the most 1069 00:44:03,980 --> 00:44:06,390 powerful pieces of the story-- 1070 00:44:06,390 --> 00:44:09,790 when your time is limited, people focus on social goals 1071 00:44:09,790 --> 00:44:13,130 related to emotional meaning and emotional satisfaction and 1072 00:44:13,130 --> 00:44:15,150 less related to knowledge acquisition. 1073 00:44:15,150 --> 00:44:19,850 That depending on the moment of your life on average, when 1074 00:44:19,850 --> 00:44:22,060 you're in adolescence, and you're in college and graduate 1075 00:44:22,060 --> 00:44:24,730 school, and you're beginning your residency, or becoming a 1076 00:44:24,730 --> 00:44:27,990 junior partner at a law firm, you're at an age of huge 1077 00:44:27,990 --> 00:44:29,180 information acquisition. 1078 00:44:29,180 --> 00:44:31,860 What you want to know is what do I need to know to do 1079 00:44:31,860 --> 00:44:33,340 something important, significant, 1080 00:44:33,340 --> 00:44:35,290 valuable in my life? 1081 00:44:35,290 --> 00:44:37,590 You're sitting here acquiring knowledge. 1082 00:44:37,590 --> 00:44:40,360 College is four years of acquiring knowledge in terms 1083 00:44:40,360 --> 00:44:42,260 of classrooms and majors. 1084 00:44:42,260 --> 00:44:43,540 You guys do other things too. 1085 00:44:43,540 --> 00:44:48,360 But the number one mission is acquire that knowledge. 1086 00:44:48,360 --> 00:44:52,090 Now when you get older, you don't really want so much 1087 00:44:52,090 --> 00:44:53,010 information anymore. 1088 00:44:53,010 --> 00:44:55,180 And maybe what you're much more interested in is how you 1089 00:44:55,180 --> 00:44:57,940 regulate your feelings, how positive can you make your 1090 00:44:57,940 --> 00:45:01,770 life, not by being adventurous, taking risks, and 1091 00:45:01,770 --> 00:45:03,690 all this kind of stuff, but by finding 1092 00:45:03,690 --> 00:45:04,810 a way towards happiness. 1093 00:45:04,810 --> 00:45:06,060 And I'm going to show you a bunch of research that 1094 00:45:06,060 --> 00:45:09,330 suggests that young adulthood is full about acquisition of 1095 00:45:09,330 --> 00:45:11,910 information through adventure. 1096 00:45:11,910 --> 00:45:16,560 And old age, on average you're focused to regulate your 1097 00:45:16,560 --> 00:45:18,730 emotions in positive ways. 1098 00:45:18,730 --> 00:45:21,220 And so sometimes people will call that wisdom. 1099 00:45:21,220 --> 00:45:23,470 Although, you could just say it's different things for 1100 00:45:23,470 --> 00:45:26,040 different ages are desirable. 1101 00:45:26,040 --> 00:45:28,780 And part of the support came from the following result, 1102 00:45:28,780 --> 00:45:30,810 which has been found many, many, many times. 1103 00:45:30,810 --> 00:45:33,290 But it was kind of stunning when it was first reported. 1104 00:45:33,290 --> 00:45:36,170 So this is where people were asked, how happy are you? 1105 00:45:36,170 --> 00:45:37,370 Are you satisfied with your life? 1106 00:45:37,370 --> 00:45:40,700 So here's a younger adults, 18 to 50 basically. 1107 00:45:40,700 --> 00:45:42,430 About half of them said they're very satisfied. 1108 00:45:42,430 --> 00:45:46,110 But it zooms up if you're older. 1109 00:45:46,110 --> 00:45:48,390 How many people are satisfied with their standard of living? 1110 00:45:48,390 --> 00:45:49,500 40 if you're younger. 1111 00:45:49,500 --> 00:45:50,990 60 if you're older. 1112 00:45:50,990 --> 00:45:54,220 Frequency of depression, for example, never. 1113 00:45:54,220 --> 00:45:56,350 Let's pick often. 1114 00:45:56,350 --> 00:45:58,785 It's higher for younger people. 1115 00:45:58,785 --> 00:46:01,570 They have more frequent thoughts about suicide. 1116 00:46:01,570 --> 00:46:05,700 By every measure you can make, if we give you a questionnaire 1117 00:46:05,700 --> 00:46:08,080 like this, on average, for 20-year-olds or 30-year-olds, 1118 00:46:08,080 --> 00:46:12,500 you would report more unhappiness than older people, 1119 00:46:12,500 --> 00:46:13,360 on average. 1120 00:46:13,360 --> 00:46:15,560 Of course, it varies. 1121 00:46:15,560 --> 00:46:18,790 But that's kind of a surprise maybe or not. 1122 00:46:18,790 --> 00:46:20,180 And everybody has found that. 1123 00:46:20,180 --> 00:46:21,040 No, not a surprise? 1124 00:46:21,040 --> 00:46:24,080 AUDIENCE: I mean, just because they report something, doesn't 1125 00:46:24,080 --> 00:46:26,656 mean that's the way it is. 1126 00:46:26,656 --> 00:46:28,430 PROFESSOR: Ah well we'll come back to this again. 1127 00:46:28,430 --> 00:46:28,800 Yes. 1128 00:46:28,800 --> 00:46:30,200 Just because you say you're happier 1129 00:46:30,200 --> 00:46:32,620 doesn't mean you're happier. 1130 00:46:32,620 --> 00:46:35,071 We don't have a better way than that though. 1131 00:46:35,071 --> 00:46:37,050 We can't say, oh, you think you're happy. 1132 00:46:37,050 --> 00:46:39,170 But you'd be so happy if you were at Caltech. 1133 00:46:39,170 --> 00:46:40,420 You'd be just so happy. 1134 00:46:43,970 --> 00:46:45,360 I'm a brain measurer. 1135 00:46:45,360 --> 00:46:47,520 So I like objective measures. 1136 00:46:47,520 --> 00:46:49,160 I think if a person tells you they're happy, 1137 00:46:49,160 --> 00:46:50,365 they probably are. 1138 00:46:50,365 --> 00:46:51,550 There are certain moments, I know, when 1139 00:46:51,550 --> 00:46:52,260 people tell you that. 1140 00:46:52,260 --> 00:46:52,770 Well, we'll see. 1141 00:46:52,770 --> 00:46:53,310 Who knows? 1142 00:46:53,310 --> 00:46:53,990 I agree with you. 1143 00:46:53,990 --> 00:46:56,140 It's a concern. 1144 00:46:56,140 --> 00:46:58,460 So here's the thought, that motivation and goals are set 1145 00:46:58,460 --> 00:46:59,500 by temporal context. 1146 00:46:59,500 --> 00:47:01,700 At times, they're perceived as limited. 1147 00:47:01,700 --> 00:47:04,160 And all this will come that the older you get, the more 1148 00:47:04,160 --> 00:47:06,840 you focus on the positive things in the world. 1149 00:47:06,840 --> 00:47:10,000 And what makes you happy is to focus on positive things and 1150 00:47:10,000 --> 00:47:11,150 ignore the negative. 1151 00:47:11,150 --> 00:47:14,250 So how true might this be experimentally? 1152 00:47:14,250 --> 00:47:16,180 So they had students-- ah, this is really washed out-- 1153 00:47:16,180 --> 00:47:19,020 capture these special moments, this same ad. 1154 00:47:19,020 --> 00:47:24,160 And this one says, "Capture the special moments." And this 1155 00:47:24,160 --> 00:47:28,630 one says, "Capture the unexplored world." 1156 00:47:28,630 --> 00:47:30,550 So if you're an information seeker, which is better? the 1157 00:47:30,550 --> 00:47:32,110 unexplored world or the special 1158 00:47:32,110 --> 00:47:34,680 moments, which is better? 1159 00:47:34,680 --> 00:47:35,580 The unexplored world, right? 1160 00:47:35,580 --> 00:47:36,450 You're a 20-year-old. 1161 00:47:36,450 --> 00:47:38,530 Unexplored Is awesome. 1162 00:47:38,530 --> 00:47:40,590 Young people prefer this ad. 1163 00:47:40,590 --> 00:47:42,490 Older people prefer the special moments. 1164 00:47:42,490 --> 00:47:45,170 And by special moments, we mean emotionally satisfying. 1165 00:47:45,170 --> 00:47:45,940 Right? 1166 00:47:45,940 --> 00:47:47,420 OK. 1167 00:47:47,420 --> 00:47:48,410 Here's another one. 1168 00:47:48,410 --> 00:47:51,110 They show you up pictures of a positive and negative 1169 00:47:51,110 --> 00:47:52,200 expression. 1170 00:47:52,200 --> 00:47:52,760 It flashes away. 1171 00:47:52,760 --> 00:47:54,740 And there's a dot left. 1172 00:47:54,740 --> 00:47:56,410 If the dot appears on the right, you push your 1173 00:47:56,410 --> 00:47:57,070 right-hand button. 1174 00:47:57,070 --> 00:47:59,160 If the dot appears on the left, you push 1175 00:47:59,160 --> 00:47:59,930 the left-hand button. 1176 00:47:59,930 --> 00:48:01,460 It's simply pushing to a dot. 1177 00:48:01,460 --> 00:48:03,960 But if the dot is in the place where you just saw, either a 1178 00:48:03,960 --> 00:48:05,530 negative or a neutral face. 1179 00:48:05,530 --> 00:48:08,110 And what they find is for younger people, they're about 1180 00:48:08,110 --> 00:48:10,760 as fast whether the dot appears where the neutral or 1181 00:48:10,760 --> 00:48:11,580 negative face was. 1182 00:48:11,580 --> 00:48:12,810 They don't really care. 1183 00:48:12,810 --> 00:48:15,910 For the older people, they're much faster if the dot appears 1184 00:48:15,910 --> 00:48:17,980 where the positive face had just been. 1185 00:48:17,980 --> 00:48:21,550 As if their attention was locked to the positive face. 1186 00:48:21,550 --> 00:48:22,590 Oh, the dot appears there. 1187 00:48:22,590 --> 00:48:24,170 I'm ready to go. 1188 00:48:24,170 --> 00:48:26,000 Locked on the positive face if the dot appears here. 1189 00:48:26,000 --> 00:48:26,890 You go, whoa, whoa, whoa. 1190 00:48:26,890 --> 00:48:28,270 You shift your attention. 1191 00:48:28,270 --> 00:48:30,240 And that takes extra time. 1192 00:48:30,240 --> 00:48:33,080 So you're locked to the positive when you see a 1193 00:48:33,080 --> 00:48:34,800 positive and a negative face. 1194 00:48:34,800 --> 00:48:37,390 Here's another one where you're doing positive and 1195 00:48:37,390 --> 00:48:38,870 negative car options, things that are good 1196 00:48:38,870 --> 00:48:40,480 or bad about a car. 1197 00:48:40,480 --> 00:48:41,250 This line goes up. 1198 00:48:41,250 --> 00:48:41,960 This line goes down. 1199 00:48:41,960 --> 00:48:44,450 Younger people focus more on the negative options relative 1200 00:48:44,450 --> 00:48:47,290 to older people who focus more on the positive options. 1201 00:48:47,290 --> 00:48:48,100 Here's another one. 1202 00:48:48,100 --> 00:48:51,190 You show pictures of happy scenes, or neutral scenes, are 1203 00:48:51,190 --> 00:48:51,950 negative scenes. 1204 00:48:51,950 --> 00:48:53,620 This is a graveyard. 1205 00:48:53,620 --> 00:48:57,180 Young people's memory for positive, negative, and 1206 00:48:57,180 --> 00:48:59,800 neutral things, they remember emotional things better. 1207 00:48:59,800 --> 00:49:00,770 Let's go to the older people. 1208 00:49:00,770 --> 00:49:02,420 Look at this line way up here. 1209 00:49:02,420 --> 00:49:04,110 That's memory for the positive scenes. 1210 00:49:04,110 --> 00:49:05,630 And here's the negative scenes. 1211 00:49:05,630 --> 00:49:08,610 Do you see the focus on the positivity and the sort of 1212 00:49:08,610 --> 00:49:11,840 lack of interest in the negative stuff? 1213 00:49:11,840 --> 00:49:14,060 For young people, equally interesting if it's positive 1214 00:49:14,060 --> 00:49:14,620 or negative. 1215 00:49:14,620 --> 00:49:17,760 For older people, much more interesting, and sticking in 1216 00:49:17,760 --> 00:49:18,950 your memory if it's positive. 1217 00:49:18,950 --> 00:49:22,690 And not sticking in your memory if it's negative. 1218 00:49:22,690 --> 00:49:24,900 So one of the big questions is, is this simply about 1219 00:49:24,900 --> 00:49:26,640 getting older? 1220 00:49:26,640 --> 00:49:29,460 And I'm going to ask you to think back, if I can, to your 1221 00:49:29,460 --> 00:49:35,220 last days in high school, your last days in high school. 1222 00:49:35,220 --> 00:49:36,940 For those last days-- 1223 00:49:36,940 --> 00:49:38,990 and I'm sure it will vary depending on your experience 1224 00:49:38,990 --> 00:49:40,836 in different ways-- 1225 00:49:40,836 --> 00:49:43,670 were you primarily interested in getting that last little 1226 00:49:43,670 --> 00:49:47,920 bit of information about US history or calculus? 1227 00:49:47,920 --> 00:49:49,040 I mean, you might have been. 1228 00:49:49,040 --> 00:49:50,560 That could have been the critical bit of information 1229 00:49:50,560 --> 00:49:53,390 that will make college work out. 1230 00:49:53,390 --> 00:49:55,560 Or did you have a sudden-- 1231 00:49:55,560 --> 00:49:58,050 and it's kind of embarrassing when you're 16, 17, 18-- 1232 00:49:58,050 --> 00:50:00,760 enhanced sense of nostalgia? 1233 00:50:00,760 --> 00:50:04,430 Oh, this is the last time the three of us, or the six of us, 1234 00:50:04,430 --> 00:50:06,510 or the eight of us, or the two of us will be together. 1235 00:50:06,510 --> 00:50:08,510 Then we're spreading across the world to go 1236 00:50:08,510 --> 00:50:10,750 to different colleges. 1237 00:50:10,750 --> 00:50:12,400 Nobody had that feeling? 1238 00:50:12,400 --> 00:50:12,750 OK. 1239 00:50:12,750 --> 00:50:14,260 It's kind of embarrassing when you're 18. 1240 00:50:14,260 --> 00:50:16,115 Because you're not supposed to say that kind of stuff. 1241 00:50:16,115 --> 00:50:18,830 And it will happen to you at the end the college for most 1242 00:50:18,830 --> 00:50:19,550 of you most of the time. 1243 00:50:19,550 --> 00:50:22,130 I remember senior year, it crept up on us in college. 1244 00:50:22,130 --> 00:50:22,900 And we started college. 1245 00:50:22,900 --> 00:50:23,360 Oh my gosh. 1246 00:50:23,360 --> 00:50:24,330 This is the last year we're together. 1247 00:50:24,330 --> 00:50:26,600 And it seemed very emotionally important. 1248 00:50:26,600 --> 00:50:27,990 So age or time. 1249 00:50:27,990 --> 00:50:29,120 So is it simply age? 1250 00:50:29,120 --> 00:50:29,910 Or is it time? 1251 00:50:29,910 --> 00:50:32,400 So they did experiments where they asked people, are you 1252 00:50:32,400 --> 00:50:34,720 focusing on adventure and content? 1253 00:50:34,720 --> 00:50:37,210 Or are you focusing on emotion and satisfaction? 1254 00:50:37,210 --> 00:50:39,260 When you're about to move from one city to another, people 1255 00:50:39,260 --> 00:50:40,910 waned to spend time with people they 1256 00:50:40,910 --> 00:50:41,860 really cared about. 1257 00:50:41,860 --> 00:50:43,120 And they were not interested in getting new information. 1258 00:50:45,820 --> 00:50:48,550 Two more tragic studies, if people are near death, and 1259 00:50:48,550 --> 00:50:50,890 they're asked this question, of course time with people, 1260 00:50:50,890 --> 00:50:52,640 not acquiring information. 1261 00:50:52,640 --> 00:50:55,620 But here's another one, inner-city gangs study in Los 1262 00:50:55,620 --> 00:50:59,340 Angeles, inner-city gangs involved in violence are much 1263 00:50:59,340 --> 00:51:03,600 more interested in time with people than in information. 1264 00:51:03,600 --> 00:51:07,300 And partly that goes with what is viewed from the outside. 1265 00:51:07,300 --> 00:51:10,610 Sometimes this kind of insane loyalty that inner-city gang 1266 00:51:10,610 --> 00:51:13,720 members have for one another is because they're so focused 1267 00:51:13,720 --> 00:51:16,450 given their situation on this relations with the other 1268 00:51:16,450 --> 00:51:19,640 people in their group compared to everything that's rational 1269 00:51:19,640 --> 00:51:24,330 about a safe growing up. 1270 00:51:24,330 --> 00:51:26,810 And, tragically, you know if you ask a member of inner-city 1271 00:51:26,810 --> 00:51:29,190 gangs how long they think they'll live, they often tell 1272 00:51:29,190 --> 00:51:30,660 you not very long. 1273 00:51:30,660 --> 00:51:33,130 I'm counting on not living very long. 1274 00:51:33,130 --> 00:51:36,580 So it's not whether you're 20, or 60, or 80. 1275 00:51:36,580 --> 00:51:39,210 It's how long you sense time is in front of 1276 00:51:39,210 --> 00:51:43,270 you, a temporal horizon. 1277 00:51:43,270 --> 00:51:46,920 Here's one study that I had a hand in. 1278 00:51:46,920 --> 00:51:49,650 We took older and younger people and put them inside an 1279 00:51:49,650 --> 00:51:52,120 MRI and show them positive, neutral, 1280 00:51:52,120 --> 00:51:52,830 and negative pictures. 1281 00:51:52,830 --> 00:51:54,530 Here's a couple different points. 1282 00:51:54,530 --> 00:51:56,730 When they said, how intense is this picture? 1283 00:51:56,730 --> 00:51:57,730 Look at younger people. 1284 00:51:57,730 --> 00:52:00,850 The positive, neutral, and the negative are really intense. 1285 00:52:00,850 --> 00:52:01,850 This goes down. 1286 00:52:01,850 --> 00:52:04,930 So the older people, as they see the pictures, experienced 1287 00:52:04,930 --> 00:52:07,780 by their own report, the negative pictures as being 1288 00:52:07,780 --> 00:52:09,020 less intense. 1289 00:52:09,020 --> 00:52:11,470 They're sort of downplaying the negative. 1290 00:52:11,470 --> 00:52:14,510 And if we asked their memory, here's younger people. 1291 00:52:14,510 --> 00:52:17,250 Positive, and negative things, neutral things, same for 1292 00:52:17,250 --> 00:52:17,950 positive and negative. 1293 00:52:17,950 --> 00:52:21,610 Look at older people, much more focused in memory, 1294 00:52:21,610 --> 00:52:23,520 retaining in memory the positive and 1295 00:52:23,520 --> 00:52:26,200 not so much the negative. 1296 00:52:26,200 --> 00:52:28,650 And if we look at their amygdala, which we know is a 1297 00:52:28,650 --> 00:52:32,360 structure that's essential for how emotion modulates the 1298 00:52:32,360 --> 00:52:35,320 formation of memory, here's young people. 1299 00:52:35,320 --> 00:52:36,520 Here's a positive picture. 1300 00:52:36,520 --> 00:52:37,440 Here's a negative picture. 1301 00:52:37,440 --> 00:52:38,140 Here's a neutral picture. 1302 00:52:38,140 --> 00:52:39,610 So emotion counts. 1303 00:52:39,610 --> 00:52:42,520 Positive and negative count about the same. 1304 00:52:42,520 --> 00:52:45,710 Look at older people. 1305 00:52:45,710 --> 00:52:47,900 Here's positive, and here's negative. 1306 00:52:47,900 --> 00:52:50,670 So this partly addresses the question for some people. 1307 00:52:50,670 --> 00:52:52,790 Are older people pretending they're positive? 1308 00:52:52,790 --> 00:52:53,940 Well, it doesn't look like that. 1309 00:52:53,940 --> 00:52:55,620 This is their amygdala as they're looking at it. 1310 00:52:55,620 --> 00:52:57,520 I don't know if their amygdala can pretend 1311 00:52:57,520 --> 00:52:59,300 to look at the positive. 1312 00:52:59,300 --> 00:53:01,390 So here's the good news for you. 1313 00:53:01,390 --> 00:53:04,620 What will happen as you get older, on average, is that for 1314 00:53:04,620 --> 00:53:08,000 whatever reason it happens-- and we don't really know why-- 1315 00:53:08,000 --> 00:53:10,050 you will focus more and more on the positive 1316 00:53:10,050 --> 00:53:11,310 things in your life. 1317 00:53:11,310 --> 00:53:15,640 And you'll feel better for that, on average. 1318 00:53:15,640 --> 00:53:18,850 So that's the kind of quiet satisfaction. 1319 00:53:18,850 --> 00:53:20,495 Now I'm focusing on the positive. 1320 00:53:20,495 --> 00:53:22,050 That's the zen satisfaction. 1321 00:53:22,050 --> 00:53:25,890 Let's talk about fantastic satisfaction, reward system. 1322 00:53:25,890 --> 00:53:28,580 When you really want to do something, because it's going 1323 00:53:28,580 --> 00:53:30,690 to feel so wonderful, the reward system. 1324 00:53:30,690 --> 00:53:32,220 So let me tell you a little bit about what we understand 1325 00:53:32,220 --> 00:53:33,550 about that. 1326 00:53:33,550 --> 00:53:36,560 It involves dopamine as the critical neurotransmitter. 1327 00:53:36,560 --> 00:53:38,700 It starts in the ventral tegmental 1328 00:53:38,700 --> 00:53:40,040 area of your brainstem. 1329 00:53:40,040 --> 00:53:42,140 And that projects to something called the nucleus accumbens, 1330 00:53:42,140 --> 00:53:44,620 an inferior portion of the basal ganglia. 1331 00:53:44,620 --> 00:53:47,330 And this is reward central. 1332 00:53:47,330 --> 00:53:51,190 If you love something from opera, to chocolate, to video 1333 00:53:51,190 --> 00:53:53,290 games, this turns on. 1334 00:53:53,290 --> 00:53:57,070 Every experiment that people have ever done shows in humans 1335 00:53:57,070 --> 00:54:00,310 if something really turns you on, this area 1336 00:54:00,310 --> 00:54:02,180 really gets turned on. 1337 00:54:02,180 --> 00:54:05,470 What's more powerful for us than what we find deeply 1338 00:54:05,470 --> 00:54:07,280 emotionally rewarding? 1339 00:54:07,280 --> 00:54:10,890 This is that rewards system. 1340 00:54:10,890 --> 00:54:13,520 And the dopamine runs from there. 1341 00:54:13,520 --> 00:54:14,690 And look at how cells respond. 1342 00:54:14,690 --> 00:54:16,490 I'm going to show you an example from monkeys where we 1343 00:54:16,490 --> 00:54:17,900 can look at single cells. 1344 00:54:17,900 --> 00:54:20,920 And then brain imaging, back to people. 1345 00:54:20,920 --> 00:54:23,020 So here's the experiment with monkeys. 1346 00:54:23,020 --> 00:54:25,600 And there's a message in this that's both biologically true 1347 00:54:25,600 --> 00:54:28,500 and compelling about human life. 1348 00:54:28,500 --> 00:54:30,850 So what's biologically true in science what's compelling 1349 00:54:30,850 --> 00:54:33,470 about life is a story. 1350 00:54:33,470 --> 00:54:34,970 So here's the experiment. 1351 00:54:34,970 --> 00:54:38,300 The monkey sits there and gets various cues, different visual 1352 00:54:38,300 --> 00:54:40,090 things that tell them what's coming up. 1353 00:54:40,090 --> 00:54:42,420 Let's pretend this is a cue that's something wonderful is 1354 00:54:42,420 --> 00:54:45,610 coming up, highly desired food. 1355 00:54:45,610 --> 00:54:47,380 So they're recording electrically why 1356 00:54:47,380 --> 00:54:48,720 the animal sees this. 1357 00:54:48,720 --> 00:54:52,490 There's waiting for what we call the anticipation period. 1358 00:54:52,490 --> 00:54:54,080 And now here comes the reward. 1359 00:54:54,080 --> 00:54:56,700 And here's something sort of deep, I think, about reward, 1360 00:54:56,700 --> 00:54:59,170 and learning, and people, and things like this. 1361 00:54:59,170 --> 00:55:01,440 So here's the neurons firing. 1362 00:55:01,440 --> 00:55:03,840 This is the sum of the neurons firing in the ventral 1363 00:55:03,840 --> 00:55:05,010 tegmental area. 1364 00:55:05,010 --> 00:55:07,230 So right now they're just sitting there. 1365 00:55:07,230 --> 00:55:10,140 Oops, here comes the reward. 1366 00:55:10,140 --> 00:55:12,610 And boom, dopamine is released. 1367 00:55:12,610 --> 00:55:14,450 The dopaminergic cells are firing like crazy. 1368 00:55:14,450 --> 00:55:15,870 They're getting food they really want. 1369 00:55:15,870 --> 00:55:17,170 We're thrilled. 1370 00:55:17,170 --> 00:55:20,150 We're hungry, and we're getting something delicious. 1371 00:55:20,150 --> 00:55:22,230 Not much more rewarding can happen when 1372 00:55:22,230 --> 00:55:23,910 you're really hungry. 1373 00:55:23,910 --> 00:55:28,110 Now they predict the arrival with the cue that you saw, a 1374 00:55:28,110 --> 00:55:31,650 meaningless stimulus. 1375 00:55:31,650 --> 00:55:32,330 And look what happens. 1376 00:55:32,330 --> 00:55:34,250 When do these neurons fire? 1377 00:55:34,250 --> 00:55:37,900 Not for the food arriving, but for the visual signal that 1378 00:55:37,900 --> 00:55:40,060 predicts the food will come. 1379 00:55:40,060 --> 00:55:44,500 What's delicious for the brain is the anticipation of 1380 00:55:44,500 --> 00:55:46,360 something that's rewarding. 1381 00:55:46,360 --> 00:55:47,843 And this morning when I was thinking about this lecture, I 1382 00:55:47,843 --> 00:55:50,370 was thinking. 1383 00:55:50,370 --> 00:55:51,370 You might say this. 1384 00:55:51,370 --> 00:55:52,765 Think about experiences you've had that you've 1385 00:55:52,765 --> 00:55:53,440 looked forward to. 1386 00:55:53,440 --> 00:55:55,710 And almost the most delicious part, you might say, is the 1387 00:55:55,710 --> 00:55:57,660 anticipation of something delightful. 1388 00:55:57,660 --> 00:56:02,600 Often the event itself is more mixed and anticlimactic than 1389 00:56:02,600 --> 00:56:03,570 you would've thought. 1390 00:56:03,570 --> 00:56:05,050 Is that fair? 1391 00:56:05,050 --> 00:56:06,950 I think there's nothing better like I'm anticipating 1392 00:56:06,950 --> 00:56:07,510 something wonderful. 1393 00:56:07,510 --> 00:56:08,910 And the event can be wonderful. 1394 00:56:08,910 --> 00:56:10,810 But often it's a little more complicated. 1395 00:56:10,810 --> 00:56:13,910 That anticipation is like pure joy, because you're 1396 00:56:13,910 --> 00:56:18,510 dopaminergic system is firing freely away. 1397 00:56:18,510 --> 00:56:20,040 And it protests also. 1398 00:56:20,040 --> 00:56:22,200 So you get the visual signal that, oh, the 1399 00:56:22,200 --> 00:56:25,300 reward's coming up. 1400 00:56:25,300 --> 00:56:26,000 Here it is. 1401 00:56:26,000 --> 00:56:27,730 Here comes the food. 1402 00:56:27,730 --> 00:56:28,960 The food doesn't come. 1403 00:56:28,960 --> 00:56:30,620 Look at the silence. 1404 00:56:30,620 --> 00:56:33,960 These cells are protesting because they didn't get what 1405 00:56:33,960 --> 00:56:36,160 they expected to get. 1406 00:56:36,160 --> 00:56:40,270 So it's very compelling that the reward in you occurs not 1407 00:56:40,270 --> 00:56:44,020 even so much for the reward itself, but the anticipation 1408 00:56:44,020 --> 00:56:47,040 of the reward is where it's biologically occurring when 1409 00:56:47,040 --> 00:56:50,120 you can anticipate and count on it correctly. 1410 00:56:50,120 --> 00:56:53,240 So, in humans, it's harder to deliver-- not impossible-- 1411 00:56:53,240 --> 00:56:54,050 food in a scanner. 1412 00:56:54,050 --> 00:56:57,010 So a very simple thing is done for a reward, which is 1413 00:56:57,010 --> 00:56:58,350 offering people money. 1414 00:56:58,350 --> 00:57:00,520 So in a given trial on a scanner, you might see a 1415 00:57:00,520 --> 00:57:01,600 meaningless cue like this. 1416 00:57:01,600 --> 00:57:06,320 But you learn that this box predicts that at the end of 1417 00:57:06,320 --> 00:57:07,340 this trial-- 1418 00:57:07,340 --> 00:57:08,430 you do many trials-- 1419 00:57:08,430 --> 00:57:09,940 you're going to get $1.00. 1420 00:57:09,940 --> 00:57:10,770 Another one might be $0.10. 1421 00:57:10,770 --> 00:57:13,090 Another one they might take away $1.00. 1422 00:57:13,090 --> 00:57:14,280 So this is like a good one to get. 1423 00:57:14,280 --> 00:57:15,945 I'm going to get $1 just sitting here. 1424 00:57:15,945 --> 00:57:17,910 I'm going to get $1. 1425 00:57:17,910 --> 00:57:18,700 It's not huge. 1426 00:57:18,700 --> 00:57:20,990 It's not the biggest reward in the world. 1427 00:57:20,990 --> 00:57:22,310 But it's something for just laying in the 1428 00:57:22,310 --> 00:57:24,830 scanner doing nothing. 1429 00:57:24,830 --> 00:57:26,840 And here's what happens. 1430 00:57:26,840 --> 00:57:29,740 Your nucleus accumbens gets activated, where dopamine 1431 00:57:29,740 --> 00:57:32,480 flows from the ventral tegmental area when you 1432 00:57:32,480 --> 00:57:34,890 anticipate a reward. 1433 00:57:34,890 --> 00:57:36,200 This is not when the reward comes. 1434 00:57:36,200 --> 00:57:39,250 This is when you're anticipating the reward. 1435 00:57:39,250 --> 00:57:41,600 Here's another picture. 1436 00:57:41,600 --> 00:57:43,560 It's most powerful for when people 1437 00:57:43,560 --> 00:57:45,350 anticipate a gain, a reward. 1438 00:57:45,350 --> 00:57:49,140 And it's less responsive when people anticipate a loss. 1439 00:57:49,140 --> 00:57:51,880 So it's about gains. 1440 00:57:51,880 --> 00:57:54,970 Then the same system projects to the inferior parts of your 1441 00:57:54,970 --> 00:57:56,980 frontal lobe. 1442 00:57:56,980 --> 00:57:59,110 So now we're moving into the neocortex. 1443 00:57:59,110 --> 00:58:01,920 And that part of the brain seems to respond most 1444 00:58:01,920 --> 00:58:04,080 powerfully if you get the reward. 1445 00:58:04,080 --> 00:58:05,970 So this is really interesting, a part of your brain that 1446 00:58:05,970 --> 00:58:07,960 responds to the anticipation, the 1447 00:58:07,960 --> 00:58:09,510 dopaminergic reward system. 1448 00:58:09,510 --> 00:58:11,660 And then another part of their brain that responds not 1449 00:58:11,660 --> 00:58:12,450 whether you anticipate it. 1450 00:58:12,450 --> 00:58:13,470 But sometimes they trick you. 1451 00:58:13,470 --> 00:58:14,470 They say we're going to give you $1. 1452 00:58:14,470 --> 00:58:14,840 And then they go, oops. 1453 00:58:14,840 --> 00:58:16,410 We're not giving it to you. 1454 00:58:16,410 --> 00:58:19,300 This part of the brain seems to register the receipt of the 1455 00:58:19,300 --> 00:58:19,960 reward or not. 1456 00:58:19,960 --> 00:58:21,710 So there's a separation of the brain between the anticipation 1457 00:58:21,710 --> 00:58:23,700 of the reward and the response to whether you get 1458 00:58:23,700 --> 00:58:24,950 the reward or not. 1459 00:58:28,100 --> 00:58:30,920 Older people, when they look at these kinds of similar 1460 00:58:30,920 --> 00:58:35,330 reward paradigms, they're less responsive to potential loss 1461 00:58:35,330 --> 00:58:36,880 but equally responsive to potential 1462 00:58:36,880 --> 00:58:38,750 gain as young adults. 1463 00:58:38,750 --> 00:58:42,060 So that's exactly responding to positive things and showing 1464 00:58:42,060 --> 00:58:46,440 less of a response to potential negative things. 1465 00:58:46,440 --> 00:58:48,440 So let's switch to adolescents. 1466 00:58:48,440 --> 00:58:50,480 We're going to focus on adolescents now mostly for the 1467 00:58:50,480 --> 00:58:53,360 next 10 minutes. 1468 00:58:53,360 --> 00:58:54,910 You just got through that. 1469 00:58:54,910 --> 00:58:57,000 So let's reflect back for the last couple of years. 1470 00:58:57,000 --> 00:58:58,680 And they make the experiments because they want to put 1471 00:58:58,680 --> 00:59:00,350 children into a little bit more of a vivid. 1472 00:59:00,350 --> 00:59:01,060 Here's pirates. 1473 00:59:01,060 --> 00:59:02,430 Here's not much reward. 1474 00:59:02,430 --> 00:59:03,040 Here's some reward. 1475 00:59:03,040 --> 00:59:05,300 Here's a lot of reward in the scanner. 1476 00:59:05,300 --> 00:59:08,830 And your children are adolescents or young adults. 1477 00:59:08,830 --> 00:59:10,340 And they look in the nucleus accumbens. 1478 00:59:10,340 --> 00:59:11,470 This is that reward region. 1479 00:59:11,470 --> 00:59:13,720 And look who's firing like crazy? 1480 00:59:13,720 --> 00:59:17,540 Adolescents, teenagers. 1481 00:59:17,540 --> 00:59:19,840 But they're not firing like crazy in the frontal cortex. 1482 00:59:22,520 --> 00:59:25,570 So this is very speculative. 1483 00:59:25,570 --> 00:59:27,990 These are partly just wide stories. 1484 00:59:27,990 --> 00:59:30,000 But one hypothesis is this. 1485 00:59:30,000 --> 00:59:33,120 And we're going to say in a minute more about this. 1486 00:59:33,120 --> 00:59:36,000 Adolescence is a really interesting period. 1487 00:59:36,000 --> 00:59:38,790 Because it's not only when you're deciding who you are in 1488 00:59:38,790 --> 00:59:40,800 the world in many ways independently. 1489 00:59:40,800 --> 00:59:44,640 It's also, worrisomely for parents, grandparents, 1490 00:59:44,640 --> 00:59:48,180 cousins, siblings, the period in life when people are most 1491 00:59:48,180 --> 00:59:51,730 likely to put themselves at great risk. 1492 00:59:51,730 --> 00:59:56,430 And one version of that is that the subcortical reward 1493 00:59:56,430 --> 01:00:01,040 areas are developing way faster than the cortical areas 1494 01:00:01,040 --> 01:00:05,970 that control and regulate your behavior. 1495 01:00:05,970 --> 01:00:09,200 This goes with the stereotype which is probably as unfair as 1496 01:00:09,200 --> 01:00:13,146 any other stereotype of the out of control teenager. 1497 01:00:13,146 --> 01:00:15,810 But imagine if it were true that your reward system is 1498 01:00:15,810 --> 01:00:17,510 very turned up. 1499 01:00:17,510 --> 01:00:20,550 And your cortical control system were not yet caught up 1500 01:00:20,550 --> 01:00:21,770 to the adult level. 1501 01:00:21,770 --> 01:00:23,730 Well, that would make you a little bit more likely to do 1502 01:00:23,730 --> 01:00:25,620 adventuresome things. 1503 01:00:25,620 --> 01:00:27,390 Because the reward is powerful. 1504 01:00:27,390 --> 01:00:30,340 And the control of your thoughts about how to approach 1505 01:00:30,340 --> 01:00:32,330 or reject that reward are less powerful. 1506 01:00:35,940 --> 01:00:38,130 So here's some things to think about. 1507 01:00:38,130 --> 01:00:41,000 And people worry about for adolescents. 1508 01:00:41,000 --> 01:00:43,970 40% of adult alcoholics report having initial alcoholism 1509 01:00:43,970 --> 01:00:45,200 between 15 and 19. 1510 01:00:45,200 --> 01:00:49,120 Between 16 and 20, both sexes are twice as likely to be in 1511 01:00:49,120 --> 01:00:51,550 accidents than drivers between 20 and 50, twice the 1512 01:00:51,550 --> 01:00:52,920 accidental rate. 1513 01:00:52,920 --> 01:00:55,270 Adolescents are more likely to engage in impulsive sexual 1514 01:00:55,270 --> 01:00:57,280 behavior and multiple partners. 1515 01:00:57,280 --> 01:00:59,770 Annually, three million adolescents contract a sexual 1516 01:00:59,770 --> 01:01:00,680 transmitted disease. 1517 01:01:00,680 --> 01:01:04,710 So lots of things that are risky behaviors occur with 1518 01:01:04,710 --> 01:01:07,830 high frequency in a demonstrable way, on average, 1519 01:01:07,830 --> 01:01:09,840 among adolescents. 1520 01:01:09,840 --> 01:01:12,150 Young kids don't drive yet. 1521 01:01:12,150 --> 01:01:15,730 20-year-olds are a bit more mature in their driving. 1522 01:01:15,730 --> 01:01:20,350 So part of this is, again, attitudinal. 1523 01:01:20,350 --> 01:01:22,720 Here's a question that people were asked about future 1524 01:01:22,720 --> 01:01:23,610 perspectives. 1525 01:01:23,610 --> 01:01:25,970 They were asked, I would rather save my money for a 1526 01:01:25,970 --> 01:01:29,930 rainy day than spend it on something fun right now. 1527 01:01:32,560 --> 01:01:34,030 In your 20s, a little bit. 1528 01:01:37,660 --> 01:01:38,700 That's growing. 1529 01:01:38,700 --> 01:01:40,020 You'll keep the dollar. 1530 01:01:40,020 --> 01:01:42,590 But the younger you are in your teenage years, the more 1531 01:01:42,590 --> 01:01:44,080 like who wants to wait. 1532 01:01:44,080 --> 01:01:46,620 Let's do it now. 1533 01:01:46,620 --> 01:01:50,660 So moving from something fun to something experimental, 1534 01:01:50,660 --> 01:01:52,910 let's put together a couple last things. 1535 01:01:52,910 --> 01:01:55,420 So here's a thing we did before several times in this 1536 01:01:55,420 --> 01:01:57,800 class, creating false memories. 1537 01:01:57,800 --> 01:01:59,950 And you remember the way they create false memories in the 1538 01:01:59,950 --> 01:02:02,870 laboratory is they pick a word they don't present to you, 1539 01:02:02,870 --> 01:02:04,072 like sweet. 1540 01:02:04,072 --> 01:02:06,960 Then they ask many students to say what words go with that 1541 01:02:06,960 --> 01:02:08,360 word, like sour, or candy, or sugar? 1542 01:02:08,360 --> 01:02:10,540 They present you this list. 1543 01:02:10,540 --> 01:02:11,940 And then they test you for this word 1544 01:02:11,940 --> 01:02:13,370 that was not presented. 1545 01:02:13,370 --> 01:02:17,890 And people often imagine incorrectly that they heard or 1546 01:02:17,890 --> 01:02:18,750 saw this word. 1547 01:02:18,750 --> 01:02:20,060 We've done that a couple of times. 1548 01:02:20,060 --> 01:02:22,700 It's a way to show illusory memory. 1549 01:02:22,700 --> 01:02:24,810 And the way we understand it is basically this. 1550 01:02:24,810 --> 01:02:29,520 Your memory, your mind, mostly thinks about the essence of 1551 01:02:29,520 --> 01:02:31,750 things, not the details of things. 1552 01:02:31,750 --> 01:02:34,790 The essence of things was everything is sweet. 1553 01:02:34,790 --> 01:02:38,820 The details were the specific words in the list. 1554 01:02:38,820 --> 01:02:43,680 So let's look at older adults versus younger adults, 1555 01:02:43,680 --> 01:02:45,450 80-year-olds versus 20-year-olds and exactly this 1556 01:02:45,450 --> 01:02:46,310 experiment. 1557 01:02:46,310 --> 01:02:48,280 Older adults have many more false memories. 1558 01:02:48,280 --> 01:02:50,110 And they perform less well. 1559 01:02:50,110 --> 01:02:54,480 So to a scary extend, the healthy 70-year-olds, here's 1560 01:02:54,480 --> 01:02:55,220 their real memories. 1561 01:02:55,220 --> 01:02:56,460 Here's their false memories. 1562 01:02:56,460 --> 01:02:58,640 It's dead even. 1563 01:02:58,640 --> 01:03:00,610 Here's young people having lots of false memories, but 1564 01:03:00,610 --> 01:03:02,380 not as many as older people, and having 1565 01:03:02,380 --> 01:03:04,010 more correct memories. 1566 01:03:04,010 --> 01:03:07,310 So older adults have more false memories, because 1567 01:03:07,310 --> 01:03:09,780 they're encoding the gist a lot, but 1568 01:03:09,780 --> 01:03:10,950 they're losing the specifics. 1569 01:03:10,950 --> 01:03:11,480 Does that make sense? 1570 01:03:11,480 --> 01:03:13,190 And you're really vulnerable to false memories. 1571 01:03:15,820 --> 01:03:17,930 Children, you might think, well children, 1572 01:03:17,930 --> 01:03:18,890 what do they know? 1573 01:03:18,890 --> 01:03:21,790 Children have less false memories than you do. 1574 01:03:21,790 --> 01:03:25,420 You would have less false memories at age five than you 1575 01:03:25,420 --> 01:03:27,640 would right now, which is kind of amazing. 1576 01:03:27,640 --> 01:03:29,220 If you didn't do the experiment, you'd imagine 1577 01:03:29,220 --> 01:03:30,880 children would be totally confused. 1578 01:03:30,880 --> 01:03:31,890 They'd get a big list of words. 1579 01:03:31,890 --> 01:03:32,830 Was sweet on the list? 1580 01:03:32,830 --> 01:03:33,190 I don't know. 1581 01:03:33,190 --> 01:03:34,660 Yeah, sure. 1582 01:03:34,660 --> 01:03:37,160 A five-year-old does better than a seven, does better than 1583 01:03:37,160 --> 01:03:40,820 an 11-year-old, does better than a 20-year-old. 1584 01:03:40,820 --> 01:03:42,200 Why? 1585 01:03:42,200 --> 01:03:44,970 Why does a five-year-old have less false memories under the 1586 01:03:44,970 --> 01:03:46,310 circumstances? 1587 01:03:46,310 --> 01:03:51,370 Well, we understand that to be the price of having a mind 1588 01:03:51,370 --> 01:03:53,180 that understands a lot of gist. 1589 01:03:53,180 --> 01:03:55,580 As you become older, you understand what's important, 1590 01:03:55,580 --> 01:03:56,090 what counts. 1591 01:03:56,090 --> 01:03:57,540 It's not the little details. 1592 01:03:57,540 --> 01:04:00,110 It's the big concepts. 1593 01:04:00,110 --> 01:04:02,900 So here's an example of, for example, how well people can 1594 01:04:02,900 --> 01:04:05,550 relate words across sentences. 1595 01:04:05,550 --> 01:04:08,590 And that grows from six to nine. 1596 01:04:08,590 --> 01:04:09,320 And that's what we want. 1597 01:04:09,320 --> 01:04:11,620 You don't want to read word, word, word. 1598 01:04:11,620 --> 01:04:15,640 You want to say, what's the point of the sentence? 1599 01:04:15,640 --> 01:04:18,380 That process of saying, I don't care about the detail. 1600 01:04:18,380 --> 01:04:23,600 I care about the concept, the gist of the concept, it's like 1601 01:04:23,600 --> 01:04:24,220 the chess players. 1602 01:04:24,220 --> 01:04:27,320 You shed the specific details to gain the 1603 01:04:27,320 --> 01:04:29,050 overall knowledge advantage. 1604 01:04:29,050 --> 01:04:32,130 But the five-year-old is not making the big picture. 1605 01:04:32,130 --> 01:04:33,440 They're just getting the little details. 1606 01:04:33,440 --> 01:04:38,395 So they're less prone to the illusory memories. 1607 01:04:38,395 --> 01:04:39,310 We can't see that. 1608 01:04:39,310 --> 01:04:41,420 But this is just showing that when it comes to organizing 1609 01:04:41,420 --> 01:04:46,650 memories, you see that develop across a childhood. 1610 01:04:46,650 --> 01:04:47,370 Last couple of things. 1611 01:04:47,370 --> 01:04:49,070 Because when I heard this a few years ago at a conference, 1612 01:04:49,070 --> 01:04:50,540 I was so surprised by these findings. 1613 01:04:50,540 --> 01:04:52,160 And I've been around long enough that i don't get as 1614 01:04:52,160 --> 01:04:54,000 surprised as often as I used to. 1615 01:04:54,000 --> 01:04:55,100 But it's kind of really interesting. 1616 01:04:55,100 --> 01:04:56,490 It's a total twist. 1617 01:04:56,490 --> 01:04:58,700 And you can make a judgment call about how 1618 01:04:58,700 --> 01:04:59,280 to interpret it. 1619 01:04:59,280 --> 01:05:01,060 But here's the experiments and the data. 1620 01:05:01,060 --> 01:05:02,770 So, again, we have this picture that everybody likes 1621 01:05:02,770 --> 01:05:06,290 because it fits with the stereotype, which is the 1622 01:05:06,290 --> 01:05:07,600 teenager out of control. 1623 01:05:07,600 --> 01:05:09,190 Their dopamine is going up. 1624 01:05:09,190 --> 01:05:12,460 And they're saying, let's do a lot of inappropriate things. 1625 01:05:12,460 --> 01:05:14,810 Because it will be rewarding. 1626 01:05:14,810 --> 01:05:16,780 I know everybody's against it. 1627 01:05:16,780 --> 01:05:17,740 So that's the stereotype. 1628 01:05:17,740 --> 01:05:19,550 And probably there's something true about that. 1629 01:05:19,550 --> 01:05:20,730 Literally, in the brain imaging, it 1630 01:05:20,730 --> 01:05:23,010 looks somewhat true. 1631 01:05:23,010 --> 01:05:24,680 But let's think about this for a moment. 1632 01:05:24,680 --> 01:05:25,760 You're going to be good at this. 1633 01:05:25,760 --> 01:05:26,660 If line a-- 1634 01:05:26,660 --> 01:05:28,960 these are lines-- is longer than b, and line b is longer 1635 01:05:28,960 --> 01:05:32,100 than line c, is a longer than c? 1636 01:05:32,100 --> 01:05:32,470 Yes. 1637 01:05:32,470 --> 01:05:32,990 All right. 1638 01:05:32,990 --> 01:05:34,240 This is MIT. 1639 01:05:37,370 --> 01:05:40,120 Now answer this question truly. 1640 01:05:40,120 --> 01:05:41,530 Think about it for a moment. 1641 01:05:41,530 --> 01:05:43,040 Person a is a friend or person b. 1642 01:05:43,040 --> 01:05:45,070 So let's pretend you're person b and your friend was a. 1643 01:05:45,070 --> 01:05:46,015 You're also a friend with c. 1644 01:05:46,015 --> 01:05:49,410 Are a and c likely to be friends? 1645 01:05:49,410 --> 01:05:50,450 Let's think about this. 1646 01:05:50,450 --> 01:05:53,660 Is it mathematically transitive like this one? 1647 01:05:53,660 --> 01:05:54,720 No. 1648 01:05:54,720 --> 01:05:56,100 Let's think about it for a moment. 1649 01:05:56,100 --> 01:06:00,630 In your experience through life, on average, are your 1650 01:06:00,630 --> 01:06:03,940 friends mostly kind of going to like each other? 1651 01:06:03,940 --> 01:06:07,800 Kind of, not all the time, but kind of? 1652 01:06:07,800 --> 01:06:08,500 Yeah, probably. 1653 01:06:08,500 --> 01:06:11,670 Because if one person likes you, and another person likes 1654 01:06:11,670 --> 01:06:12,620 you, you share interests. 1655 01:06:12,620 --> 01:06:15,660 You share background to a certain extent, in a loose 1656 01:06:15,660 --> 01:06:16,610 statistical way. 1657 01:06:16,610 --> 01:06:17,840 It's not definitive like this. 1658 01:06:17,840 --> 01:06:19,250 So let's take a look at what happens when you ask you two 1659 01:06:19,250 --> 01:06:21,890 questions to grades one through four. 1660 01:06:21,890 --> 01:06:23,950 OK, these kids are just making mistakes. 1661 01:06:23,950 --> 01:06:24,920 And they're getting smarter. 1662 01:06:24,920 --> 01:06:28,120 But look at this one go up just like that. 1663 01:06:28,120 --> 01:06:32,050 So we can say this is a growth in logical ability. 1664 01:06:32,050 --> 01:06:36,120 This is a growth in your everyday sense that I hang out 1665 01:06:36,120 --> 01:06:37,540 with a certain kind of person. 1666 01:06:37,540 --> 01:06:39,130 Maybe they like football. 1667 01:06:39,130 --> 01:06:41,590 Maybe they like skating. 1668 01:06:41,590 --> 01:06:43,750 Maybe they like psychology. 1669 01:06:43,750 --> 01:06:45,520 but that's the group I tend to hang out with. 1670 01:06:45,520 --> 01:06:49,630 And, on average, if I have a friend, it's because we share 1671 01:06:49,630 --> 01:06:52,370 some interests, or style of being. 1672 01:06:52,370 --> 01:06:54,480 And if I have another friend, we probably share that too. 1673 01:06:54,480 --> 01:07:00,790 So more than chance, they might like each other. 1674 01:07:00,790 --> 01:07:03,460 So this is this idea that you can separate out what you 1675 01:07:03,460 --> 01:07:07,600 might call purely logical analysis of things versus a 1676 01:07:07,600 --> 01:07:10,930 growth of social experience, basically. 1677 01:07:10,930 --> 01:07:14,240 So the last three slides or so. 1678 01:07:14,240 --> 01:07:16,520 You remember this from a bit back, from a prior example. 1679 01:07:16,520 --> 01:07:18,000 We said there's a framing heuristic. 1680 01:07:21,210 --> 01:07:22,550 People are risk averse for gains. 1681 01:07:22,550 --> 01:07:24,370 But they're risk-taking for losses. 1682 01:07:24,370 --> 01:07:25,750 If we said here's a program. 1683 01:07:25,750 --> 01:07:26,810 We did this before. 1684 01:07:26,810 --> 01:07:31,760 If Program A is adopted, 200 people are saved. 1685 01:07:31,760 --> 01:07:33,760 Or here's 400 people will die out of 600. 1686 01:07:33,760 --> 01:07:35,630 That's the same statement. 1687 01:07:35,630 --> 01:07:39,400 But because this is stated as a gain, people 1688 01:07:39,400 --> 01:07:40,520 usually like this. 1689 01:07:40,520 --> 01:07:42,980 Because this is stated as a loss, people 1690 01:07:42,980 --> 01:07:44,180 usually don't like this. 1691 01:07:44,180 --> 01:07:47,750 Adults are risk averse for gains, and they're risk-taking 1692 01:07:47,750 --> 01:07:48,295 for losses. 1693 01:07:48,295 --> 01:07:50,570 If something looks like a loss, roll the dice. 1694 01:07:50,570 --> 01:07:53,370 If something looks like it's going to work out, go with it, 1695 01:07:53,370 --> 01:07:55,170 even though numerically, these are identical. 1696 01:07:58,500 --> 01:07:59,400 You can't see this. 1697 01:07:59,400 --> 01:08:01,040 I can tell you. 1698 01:08:01,040 --> 01:08:04,190 It's not present in 1699 01:08:04,190 --> 01:08:06,160 preschoolers or second graders. 1700 01:08:06,160 --> 01:08:08,390 Preschoolers or second graders, when you give them 1701 01:08:08,390 --> 01:08:11,960 these kinds of problems, they don't show the asymmetry for 1702 01:08:11,960 --> 01:08:13,560 losses and gains. 1703 01:08:13,560 --> 01:08:15,940 That's something that happens over time. 1704 01:08:15,940 --> 01:08:16,950 And it's not a logical one. 1705 01:08:16,950 --> 01:08:18,450 Logically, it should be that. 1706 01:08:18,450 --> 01:08:22,330 So in that weird sense, the preschooler is more logical 1707 01:08:22,330 --> 01:08:25,979 than you and I, more logical than you and I. Because 1708 01:08:25,979 --> 01:08:27,830 there's no reason to be statistically different for 1709 01:08:27,830 --> 01:08:28,689 losses and gains. 1710 01:08:28,689 --> 01:08:32,250 That's purely an attitudinal emotional perspective. 1711 01:08:32,250 --> 01:08:33,680 First of all, you can hear the information-seeking. 1712 01:08:33,680 --> 01:08:34,460 Let's check it out. 1713 01:08:34,460 --> 01:08:37,770 That's kind of interesting, swimming with sharks. 1714 01:08:37,770 --> 01:08:40,830 I can assure you 70-year-olds are not going to go, hey, that 1715 01:08:40,830 --> 01:08:41,539 can be kind of interesting. 1716 01:08:41,539 --> 01:08:42,370 They're going, no! 1717 01:08:42,370 --> 01:08:42,840 Terrible idea! 1718 01:08:42,840 --> 01:08:43,770 Don't do it! 1719 01:08:43,770 --> 01:08:46,006 Yeah? 1720 01:08:46,006 --> 01:08:48,880 AUDIENCE: Were they asked in a group collectively? 1721 01:08:48,880 --> 01:08:49,359 PROFESSOR: Yeah. 1722 01:08:49,359 --> 01:08:51,540 You see some peer influence. 1723 01:08:51,540 --> 01:08:52,310 Yeah. 1724 01:08:52,310 --> 01:08:54,290 And that doesn't happen with adolescents, right? 1725 01:08:58,890 --> 01:08:59,170 They do this. 1726 01:08:59,170 --> 01:08:59,990 They go, oh my gosh. 1727 01:08:59,990 --> 01:09:01,550 These are these teenagers who are going to go do all these 1728 01:09:01,550 --> 01:09:03,870 things, and get horrible sexual diseases, and drive 1729 01:09:03,870 --> 01:09:05,149 while they are impaired. 1730 01:09:05,149 --> 01:09:08,420 And that's just the beginning of their weekend. 1731 01:09:08,420 --> 01:09:10,370 Because they're not going to follow all the advice that we 1732 01:09:10,370 --> 01:09:11,950 gave them for years, and years, and years, and years, 1733 01:09:11,950 --> 01:09:13,510 at home and in school. 1734 01:09:13,510 --> 01:09:15,170 So here's the flip on this. 1735 01:09:15,170 --> 01:09:17,430 And just think about it for a moment. 1736 01:09:17,430 --> 01:09:19,100 It's complicated. 1737 01:09:19,100 --> 01:09:22,350 Swimming with sharks, the adults say, you don't have to 1738 01:09:22,350 --> 01:09:23,050 tell me any more. 1739 01:09:23,050 --> 01:09:24,300 It's a bad idea. 1740 01:09:24,300 --> 01:09:27,160 The gist is sharks, bad. 1741 01:09:27,160 --> 01:09:29,450 I don't even need to hear the rest of the story. 1742 01:09:29,450 --> 01:09:31,890 Adolescents start to weigh the factors. 1743 01:09:31,890 --> 01:09:33,140 We'd be safer in a group. 1744 01:09:33,140 --> 01:09:35,620 Is it dark or night outside? 1745 01:09:35,620 --> 01:09:38,370 How shallow is the water? 1746 01:09:38,370 --> 01:09:40,500 And you can say, well, it's kind of ridiculous. 1747 01:09:40,500 --> 01:09:42,120 But it's not totally ridiculous. 1748 01:09:42,120 --> 01:09:44,500 Because when we talk about danger, those are some of the 1749 01:09:44,500 --> 01:09:46,109 things you might start to think about. 1750 01:09:46,109 --> 01:09:51,109 So by this analysis, having unprotected sex. 1751 01:09:51,109 --> 01:09:53,939 Adults, bad, bad, bad. 1752 01:09:53,939 --> 01:09:54,510 OK? 1753 01:09:54,510 --> 01:09:56,280 I mean really bad. 1754 01:09:56,280 --> 01:10:00,700 Adolescents, well, let's think about this. 1755 01:10:00,700 --> 01:10:01,350 What's the gain? 1756 01:10:01,350 --> 01:10:05,660 Well, we hear that sex is highly pleasurable. 1757 01:10:05,660 --> 01:10:07,000 What's the loss? 1758 01:10:07,000 --> 01:10:09,120 All these things everybody's telling us. 1759 01:10:09,120 --> 01:10:13,030 What's the odds, purely statistically, that for a 1760 01:10:13,030 --> 01:10:17,400 single, sexual experience, you will have the pleasure of sex, 1761 01:10:17,400 --> 01:10:20,360 but you will end up with a terrible disease? 1762 01:10:20,360 --> 01:10:22,135 What's the odds for one outing? 1763 01:10:24,980 --> 01:10:26,230 What do you think? 1764 01:10:28,540 --> 01:10:30,080 Here's the complexity. 1765 01:10:30,080 --> 01:10:32,450 Some people argue that adolescents are actually more 1766 01:10:32,450 --> 01:10:34,310 accurate in their assessment of risk, not 1767 01:10:34,310 --> 01:10:35,720 wise in their choice. 1768 01:10:35,720 --> 01:10:37,490 Do you understand the point? 1769 01:10:37,490 --> 01:10:40,280 They're actually doing the calculations, whereas adults 1770 01:10:40,280 --> 01:10:42,170 just go, sharks bad. 1771 01:10:42,170 --> 01:10:45,690 Sexually transmitted diseases, avoid. 1772 01:10:45,690 --> 01:10:48,450 You're not parsing through the exact odds and circumstances, 1773 01:10:48,450 --> 01:10:51,070 the trade-offs between exploration and pleasure and 1774 01:10:51,070 --> 01:10:52,720 responsibility and safety. 1775 01:10:52,720 --> 01:10:55,280 You just have the gist, the line, that's it. 1776 01:10:55,280 --> 01:10:57,170 That's my wisdom that I've gotten. 1777 01:10:57,170 --> 01:10:57,900 Sharks, bad. 1778 01:10:57,900 --> 01:10:59,720 Sexually transmitted disease, bad. 1779 01:10:59,720 --> 01:11:01,520 That's it. 1780 01:11:01,520 --> 01:11:03,790 And these teenagers are kind of curiously thinking about 1781 01:11:03,790 --> 01:11:04,430 what are the factors. 1782 01:11:04,430 --> 01:11:06,270 And you could say, it's not the best analysis. 1783 01:11:06,270 --> 01:11:08,960 But you could say it's almost more rational. 1784 01:11:08,960 --> 01:11:13,000 Just like the older adults will make more gist errors in 1785 01:11:13,000 --> 01:11:15,600 memory, they will be more emotional in their 1786 01:11:15,600 --> 01:11:18,130 avoidance of risk. 1787 01:11:18,130 --> 01:11:19,550 So it's very complicated. 1788 01:11:19,550 --> 01:11:21,540 It's not just dopamine flushing. 1789 01:11:21,540 --> 01:11:22,950 It's also in the brain. 1790 01:11:22,950 --> 01:11:25,840 It's also something about how risk is perceived at different 1791 01:11:25,840 --> 01:11:27,820 ages and what information is available to you. 1792 01:11:27,820 --> 01:11:28,220 All right. 1793 01:11:28,220 --> 01:11:29,470 Thanks very much.