1 00:00:05,200 --> 00:00:07,320 Speaker 1: If you take a look at a brain, how can 2 00:00:07,360 --> 00:00:11,080 Speaker 1: you tell immediately if it belongs to a piano player 3 00:00:11,480 --> 00:00:15,200 Speaker 1: or a violinist? How can a dog learn to walk 4 00:00:15,280 --> 00:00:18,320 Speaker 1: on its rear legs like a human? And what does 5 00:00:18,360 --> 00:00:21,840 Speaker 1: this have to do with how you become an expert 6 00:00:21,920 --> 00:00:25,800 Speaker 1: at something? Or what would happen if Venus and Serena 7 00:00:25,840 --> 00:00:30,400 Speaker 1: Williams had a hypothetical brother, Fred who hated tennis? And 8 00:00:30,480 --> 00:00:35,120 Speaker 1: how do governments respond to change just like brains do? 9 00:00:35,880 --> 00:00:39,639 Speaker 1: And finally, why am I so optimistic about the brains 10 00:00:39,840 --> 00:00:46,519 Speaker 1: of digital natives. Welcome to the inner Cosmos with me 11 00:00:46,680 --> 00:00:50,599 Speaker 1: David Eagleman. I'm a neuroscientist and author at Stanford and 12 00:00:50,720 --> 00:00:54,280 Speaker 1: in these episodes we sail deeply into our three pound 13 00:00:54,360 --> 00:00:58,480 Speaker 1: universe to understand why and how our lives look. 14 00:00:58,360 --> 00:00:59,120 Speaker 2: The way they do. 15 00:01:08,200 --> 00:01:12,520 Speaker 1: Today's episode is about brain plasticity, which is the ability 16 00:01:12,560 --> 00:01:16,240 Speaker 1: of the brain to change and adapt throughout your life. 17 00:01:16,760 --> 00:01:20,840 Speaker 1: The word plasticity comes from the word plastic, which is 18 00:01:20,840 --> 00:01:24,000 Speaker 1: a material that you can mold into any shape and 19 00:01:24,040 --> 00:01:26,679 Speaker 1: then it holds onto that shape. And that is what 20 00:01:26,760 --> 00:01:30,320 Speaker 1: is impressive about brains. You can expose them to any 21 00:01:30,360 --> 00:01:34,360 Speaker 1: kind of situation or experience, and they hold on to 22 00:01:34,560 --> 00:01:38,480 Speaker 1: the change. The vast forest of neurons in your head, 23 00:01:38,840 --> 00:01:43,640 Speaker 1: These connections change their strength, and sometimes they unplug and 24 00:01:43,680 --> 00:01:46,960 Speaker 1: they seek around and they replug in somewhere else. It's 25 00:01:47,000 --> 00:01:51,360 Speaker 1: a living forest of eighty six billion neurons in your head, 26 00:01:51,680 --> 00:01:57,840 Speaker 1: and this constant reconfiguration, this is how you learn and remember. 27 00:01:58,960 --> 00:02:01,680 Speaker 1: The interesting part I want to address today is exactly 28 00:02:02,240 --> 00:02:04,960 Speaker 1: when these changes in the brain happened, because it's not 29 00:02:05,560 --> 00:02:08,280 Speaker 1: all the time. Most of the stuff that happens in 30 00:02:08,280 --> 00:02:11,360 Speaker 1: your life makes no change at all to your brain. 31 00:02:12,040 --> 00:02:14,920 Speaker 1: So what's the difference between the stuff that sticks and 32 00:02:14,960 --> 00:02:19,280 Speaker 1: the stuff that doesn't. So let's start today in Hungary 33 00:02:19,720 --> 00:02:23,959 Speaker 1: with an educational psychologist named Laslow Polgar. The thing about 34 00:02:24,040 --> 00:02:27,920 Speaker 1: Laslow is that he loves chess, and he's written some 35 00:02:27,960 --> 00:02:31,200 Speaker 1: well known chess books. But that's not the super interesting 36 00:02:31,240 --> 00:02:33,640 Speaker 1: thing about him. The super interesting thing is that he 37 00:02:33,720 --> 00:02:38,080 Speaker 1: got very interested in the theory of child rearing and 38 00:02:38,160 --> 00:02:43,440 Speaker 1: he believed quote, geniuses are made, not born. So he 39 00:02:43,520 --> 00:02:47,320 Speaker 1: started preparing himself for fatherhood even before he had a spouse, 40 00:02:47,720 --> 00:02:52,160 Speaker 1: and he read the biographies of four hundred famous intellectuals 41 00:02:52,160 --> 00:02:55,799 Speaker 1: like Socrates and Einstein, and he noted that what they 42 00:02:55,880 --> 00:03:00,000 Speaker 1: all had in common is they started their intellectual pursuits 43 00:03:00,120 --> 00:03:04,160 Speaker 1: at a young age and they studied intensively. So he 44 00:03:04,240 --> 00:03:08,360 Speaker 1: concluded from this research the idea that he could, with 45 00:03:08,480 --> 00:03:13,240 Speaker 1: the right effort, turn his future children into geniuses in 46 00:03:13,280 --> 00:03:16,280 Speaker 1: a particular area which he and his wife could think 47 00:03:16,280 --> 00:03:19,960 Speaker 1: about and pick. So they considered various domains, but they 48 00:03:20,080 --> 00:03:25,200 Speaker 1: chose chess in part because the success of these children 49 00:03:25,240 --> 00:03:28,480 Speaker 1: could be easily measurable with chess. So he and his 50 00:03:28,520 --> 00:03:33,440 Speaker 1: wife had three daughters together, Susan, Sophia and Judete, and 51 00:03:33,480 --> 00:03:36,280 Speaker 1: he made the move, which was unusual in Hungary at 52 00:03:36,280 --> 00:03:39,640 Speaker 1: the time, to homeschool them, and he taught them German 53 00:03:39,680 --> 00:03:42,280 Speaker 1: and English and Russian and high level math, but he 54 00:03:42,360 --> 00:03:46,520 Speaker 1: primarily taught them chess from the moment that they were 55 00:03:46,520 --> 00:03:48,119 Speaker 1: big enough to play with the pieces. 56 00:03:49,080 --> 00:03:50,720 Speaker 2: So what was the result. 57 00:03:51,400 --> 00:03:55,280 Speaker 1: By the time his eldest daughter, Susan turned fifteen years old, 58 00:03:55,920 --> 00:03:58,960 Speaker 1: she was the top ranked chess player in the world. 59 00:03:59,520 --> 00:04:01,960 Speaker 1: In nineteen teen eighty six, she qualified for the men's 60 00:04:01,960 --> 00:04:05,600 Speaker 1: World Championship, which was a first time achievement for a female, 61 00:04:05,920 --> 00:04:08,720 Speaker 1: and within five years she had earned the men's Grand 62 00:04:08,840 --> 00:04:14,720 Speaker 1: Master title and then in the middle of Susan's astounding accomplishments, 63 00:04:14,760 --> 00:04:18,960 Speaker 1: Her fourteen year old middle sister, Sophia, achieved fame for 64 00:04:19,120 --> 00:04:23,000 Speaker 1: her sack of Rome, which was her stunning victory at 65 00:04:23,040 --> 00:04:25,800 Speaker 1: a tournament in Italy, which ranked as one of the 66 00:04:25,920 --> 00:04:30,000 Speaker 1: strongest performances ever by a fourteen year old. Sofia went 67 00:04:30,040 --> 00:04:34,480 Speaker 1: on to become an international master and a woman grand master. 68 00:04:35,480 --> 00:04:36,200 Speaker 2: And then there was. 69 00:04:36,160 --> 00:04:40,320 Speaker 1: The youngest sister, Judite, who is widely considered the best 70 00:04:40,320 --> 00:04:45,160 Speaker 1: female chess player on record. She achieved grand master status 71 00:04:45,640 --> 00:04:48,240 Speaker 1: at the tender age of fifteen years and four months, 72 00:04:48,640 --> 00:04:51,160 Speaker 1: and she remains the only woman on the World Chess 73 00:04:51,200 --> 00:04:54,200 Speaker 1: Federation's Top one hundred list, and for a while she 74 00:04:54,680 --> 00:04:58,960 Speaker 1: held a position in the top ten. So what accounts 75 00:04:58,960 --> 00:05:03,000 Speaker 1: for their success, Well, their parents trained the girls every 76 00:05:03,040 --> 00:05:05,880 Speaker 1: single day. They didn't just expose them to chess, they 77 00:05:06,400 --> 00:05:07,560 Speaker 1: fed them on chess. 78 00:05:07,920 --> 00:05:10,839 Speaker 2: The girls received hugs. 79 00:05:10,320 --> 00:05:15,120 Speaker 1: And stern looks and approval and attention based on their 80 00:05:15,200 --> 00:05:19,120 Speaker 1: chess performance, and as a result, their brains came to 81 00:05:19,240 --> 00:05:24,200 Speaker 1: have a great deal of circuitry devoted to chess. Now, 82 00:05:24,279 --> 00:05:27,719 Speaker 1: we've seen in other episodes how the brain is always 83 00:05:27,800 --> 00:05:32,400 Speaker 1: rewriting itself in response to its inputs. But the fact 84 00:05:32,520 --> 00:05:36,719 Speaker 1: is that not all information streaming into the pipelines is 85 00:05:36,800 --> 00:05:42,280 Speaker 1: equally important. How brains adjust themselves has everything to do 86 00:05:42,400 --> 00:05:46,880 Speaker 1: with what you're spending your time on, and that's why 87 00:05:46,920 --> 00:05:51,880 Speaker 1: the Polgar sisters became biological chess machines. And it's the 88 00:05:51,880 --> 00:05:56,680 Speaker 1: same thing with your brain. It'll reconfigure to whatever you're doing. 89 00:05:56,839 --> 00:06:02,160 Speaker 1: So if you decide to make a career change to ornithology, 90 00:06:02,200 --> 00:06:06,160 Speaker 1: the study of birds, more of your neural resources will 91 00:06:06,200 --> 00:06:10,960 Speaker 1: become devoted towards learning the subtle differences between birds, like 92 00:06:11,000 --> 00:06:15,719 Speaker 1: their wing shape, or their breast coloration, or their beak size, 93 00:06:16,120 --> 00:06:21,080 Speaker 1: while maybe previously your neural representation of birds with something 94 00:06:21,120 --> 00:06:24,760 Speaker 1: more crude, like is that a birder and airplane. So 95 00:06:24,880 --> 00:06:28,640 Speaker 1: let's dive in to unpack how the brain makes changes 96 00:06:28,720 --> 00:06:31,680 Speaker 1: and when it doesn't, which will tell us everything we 97 00:06:31,720 --> 00:06:35,159 Speaker 1: need to know about how to make changes stick in 98 00:06:35,279 --> 00:06:39,839 Speaker 1: your own brain. There's a great story about the violinist 99 00:06:39,920 --> 00:06:44,880 Speaker 1: Yetsak Pearlman after one of his concerts and admiring concertgoer 100 00:06:45,000 --> 00:06:48,440 Speaker 1: said to him, I would give my life to play 101 00:06:48,560 --> 00:06:53,320 Speaker 1: like that, and Pearlman said, I did, Now what did 102 00:06:53,360 --> 00:06:57,120 Speaker 1: he mean? Well, every morning, Pearlman drags himself out of 103 00:06:57,120 --> 00:07:00,360 Speaker 1: bed at five point fifteen. He takes a shower and batakfast, 104 00:07:00,680 --> 00:07:03,839 Speaker 1: and then digs into his four and a half hour 105 00:07:04,080 --> 00:07:07,720 Speaker 1: morning practice. He then takes a lunch and an exercise session, 106 00:07:08,160 --> 00:07:12,480 Speaker 1: and then launches his afternoon practice for another four and 107 00:07:12,480 --> 00:07:15,400 Speaker 1: a half hours. He does this every day of the year, 108 00:07:15,880 --> 00:07:18,640 Speaker 1: except for concert days, when he does only the morning 109 00:07:18,680 --> 00:07:23,600 Speaker 1: practice session. And you know what, Brain circuitry comes to 110 00:07:23,640 --> 00:07:28,520 Speaker 1: reflect what you do. So the cortex of Jasah Pearlman, 111 00:07:28,800 --> 00:07:33,760 Speaker 1: or any highly trained musician changes through time into something different. 112 00:07:33,840 --> 00:07:38,120 Speaker 1: And this isn't a metaphorical claim. You can see this 113 00:07:38,240 --> 00:07:41,160 Speaker 1: with brain imaging, even with an untrained eye. 114 00:07:41,520 --> 00:07:42,400 Speaker 2: Let me tell you how. 115 00:07:42,720 --> 00:07:46,000 Speaker 1: If you look at the strip of brain right underneath 116 00:07:46,000 --> 00:07:49,560 Speaker 1: where you wear headphones, that's an area called the motor cortex, 117 00:07:50,000 --> 00:07:53,080 Speaker 1: and that's what directs your body how to move all 118 00:07:53,120 --> 00:07:58,000 Speaker 1: of its six hundred exquisitely beautiful muscles. Now, if you 119 00:07:58,200 --> 00:08:01,360 Speaker 1: zoom in on a region of the cortex involved in 120 00:08:01,840 --> 00:08:05,880 Speaker 1: hand movement, you'll find something amazing, which is that musicians 121 00:08:06,360 --> 00:08:09,800 Speaker 1: have a little puckered shape on their cortex where non 122 00:08:09,880 --> 00:08:13,920 Speaker 1: musicians don't. So think of it like an extra wrinkle 123 00:08:14,160 --> 00:08:16,960 Speaker 1: on the wrinkly outer bit of the brain, the cortex. 124 00:08:17,440 --> 00:08:18,880 Speaker 2: Why do the musicians have this. 125 00:08:19,280 --> 00:08:23,680 Speaker 1: It's because they use the muscles of their hands in 126 00:08:23,720 --> 00:08:28,280 Speaker 1: an extraordinarily detailed way, much more so than non musicians, 127 00:08:28,880 --> 00:08:29,560 Speaker 1: so their. 128 00:08:29,360 --> 00:08:32,680 Speaker 2: Brains devote more real estate to that task. 129 00:08:33,200 --> 00:08:37,880 Speaker 1: The thousands of hours of practice on the instrument physically 130 00:08:37,960 --> 00:08:42,400 Speaker 1: molds their brains. And by the way, this is wildly specific. 131 00:08:42,640 --> 00:08:46,760 Speaker 1: So imagine that you compare the brain of a violinist 132 00:08:46,880 --> 00:08:51,640 Speaker 1: like Pearlman to the brain of a pianist like Vladimir Ashkenazi. 133 00:08:52,160 --> 00:08:56,000 Speaker 1: What they both have in common is a deep dedication 134 00:08:56,120 --> 00:08:59,360 Speaker 1: to their craft and countless hours of practice, and yet 135 00:09:00,160 --> 00:09:04,520 Speaker 1: their brains look sufficiently different that you can easily see 136 00:09:04,920 --> 00:09:10,040 Speaker 1: which brain belongs to whom. And that's because string players 137 00:09:10,120 --> 00:09:14,000 Speaker 1: like Pearlman show that extra wrinkle mostly on one side 138 00:09:14,000 --> 00:09:17,600 Speaker 1: and one hemisphere, because his left fingers are doing all 139 00:09:17,600 --> 00:09:20,680 Speaker 1: the detailed work while the right hand mostly just runs 140 00:09:20,720 --> 00:09:24,760 Speaker 1: the bow over the strings. In contrast, a pianist like 141 00:09:24,840 --> 00:09:29,600 Speaker 1: Ashkenazi has that extra wrinkle in both hemispheres because both 142 00:09:29,640 --> 00:09:33,760 Speaker 1: of his hands are performing meticulous patterns on the ivories. 143 00:09:34,520 --> 00:09:38,079 Speaker 1: So simply by looking at the brain which used to 144 00:09:38,120 --> 00:09:39,800 Speaker 1: be done in autopsy, but now you can do with 145 00:09:39,840 --> 00:09:44,160 Speaker 1: a brain scan. You can tell what kind of musician 146 00:09:44,240 --> 00:09:46,480 Speaker 1: you have in the scanner. You can discern this just 147 00:09:46,520 --> 00:09:51,199 Speaker 1: by looking at the wrinkly bits on the motor cortex. 148 00:09:51,840 --> 00:09:55,160 Speaker 2: And we can read even more from the brain's patterns. 149 00:09:55,600 --> 00:09:58,720 Speaker 1: It represents not only that a hand is doing less 150 00:09:58,800 --> 00:10:01,280 Speaker 1: or more, but sometimes what what in particular it's doing. 151 00:10:01,559 --> 00:10:04,240 Speaker 1: So let's say you get a job at an assembly 152 00:10:04,320 --> 00:10:07,520 Speaker 1: line and you're randomly assigned to one of two jobs. 153 00:10:07,559 --> 00:10:12,400 Speaker 1: Either you put little marbles into jars, or your job 154 00:10:12,480 --> 00:10:16,240 Speaker 1: is to screw the jar lid shut. Okay, so both 155 00:10:16,320 --> 00:10:20,480 Speaker 1: jobs use your right hand, but the first requires fine 156 00:10:20,720 --> 00:10:24,360 Speaker 1: use of your fingertips, while screwing the lid on makes 157 00:10:24,440 --> 00:10:27,679 Speaker 1: use of your wrist and forearm. So if you're the 158 00:10:28,240 --> 00:10:32,160 Speaker 1: jar filler, the real estate in your cortex that represents 159 00:10:32,200 --> 00:10:36,360 Speaker 1: your fingers will increase, and this is at the expense 160 00:10:36,400 --> 00:10:38,559 Speaker 1: of the real estate devoted to your wrists and forearms. 161 00:10:39,240 --> 00:10:42,680 Speaker 1: If you are the lid turner, the opposite happens. You 162 00:10:42,760 --> 00:10:47,360 Speaker 1: get more representation for your wrist and forearm and less 163 00:10:47,559 --> 00:10:51,240 Speaker 1: for the detailed movement of your fingers. So in this way, 164 00:10:51,600 --> 00:10:55,760 Speaker 1: what you do over and over becomes reflected in the 165 00:10:55,800 --> 00:11:00,360 Speaker 1: structure of your brain, and these changes involve more than 166 00:11:00,400 --> 00:11:01,520 Speaker 1: the motor cortex. 167 00:11:01,600 --> 00:11:02,960 Speaker 2: For example, if. 168 00:11:02,800 --> 00:11:06,760 Speaker 1: You spend months learning to read Braille, the bit of 169 00:11:06,800 --> 00:11:10,640 Speaker 1: your cortex that represents touch from the index finger that 170 00:11:10,720 --> 00:11:14,720 Speaker 1: will grow. If you take up juggling as an adult, 171 00:11:15,160 --> 00:11:18,800 Speaker 1: the visual areas of your brain involved in that they increase. 172 00:11:19,640 --> 00:11:23,720 Speaker 1: This is because brains reflect not simply the outside world, 173 00:11:23,800 --> 00:11:28,800 Speaker 1: but more specifically your outside world, and this is what 174 00:11:29,080 --> 00:11:34,680 Speaker 1: underlies getting good at something. Professional tennis players like Serena 175 00:11:34,720 --> 00:11:37,679 Speaker 1: and Venus Williams they spend years training so that the 176 00:11:37,800 --> 00:11:47,880 Speaker 1: right moves will come automatically in the heat of the game. Step, pivot, backhand, charge, fallback, aim, smash. 177 00:11:48,240 --> 00:11:49,000 Speaker 2: They train for. 178 00:11:49,200 --> 00:11:53,040 Speaker 1: Thousands of hours to burn the moves down into the 179 00:11:53,120 --> 00:11:57,640 Speaker 1: unconscious circuitry of the brain. They craft their brains into 180 00:11:57,679 --> 00:12:01,920 Speaker 1: overtrained machinery. He might have heard of the ten thousand 181 00:12:02,000 --> 00:12:04,839 Speaker 1: hour rule, which suggests that you need to practice a 182 00:12:04,920 --> 00:12:08,319 Speaker 1: skill for that many hours to become an expert, whether 183 00:12:08,360 --> 00:12:12,360 Speaker 1: this is surfboarding or spelunking, or saxophone playing or whatever. 184 00:12:13,160 --> 00:12:16,960 Speaker 1: Although we can't quantify the exact number of hours, the 185 00:12:17,080 --> 00:12:21,120 Speaker 1: general idea is correct. You need massive amounts of repetition 186 00:12:21,679 --> 00:12:26,280 Speaker 1: to dig the subway maps of the brain. There's a 187 00:12:26,320 --> 00:12:28,719 Speaker 1: guy that I mentioned in an earlier episode. His name 188 00:12:28,720 --> 00:12:32,000 Speaker 1: is Destin Sandlin, and he made a video where he 189 00:12:32,080 --> 00:12:35,400 Speaker 1: tries to ride a bike that someone gave him with 190 00:12:35,720 --> 00:12:39,680 Speaker 1: reversed steering, so when you push the handlebars to the left, 191 00:12:40,000 --> 00:12:42,680 Speaker 1: the wheel turns to the right and vice versa. This 192 00:12:42,840 --> 00:12:45,839 Speaker 1: is a super difficult thing to learn how to ride. 193 00:12:46,520 --> 00:12:49,439 Speaker 1: So what he did is he spent every day working 194 00:12:49,480 --> 00:12:52,920 Speaker 1: on this and trying it out, and he crashed and crashed, 195 00:12:52,960 --> 00:12:56,520 Speaker 1: but eventually he got it. But the point I want 196 00:12:56,559 --> 00:12:59,080 Speaker 1: to make here is that you know, he's an engineer, 197 00:12:59,400 --> 00:13:02,719 Speaker 1: and it only took him a few seconds to cognitively 198 00:13:02,960 --> 00:13:08,440 Speaker 1: understand how the bike worked, but that proved insufficient to 199 00:13:08,640 --> 00:13:13,000 Speaker 1: ride it. He needed to invest weeks and weeks of practice. 200 00:13:13,679 --> 00:13:16,160 Speaker 2: Hence the ten thousand hour rule. 201 00:13:17,160 --> 00:13:21,599 Speaker 1: And this dynamic changing of the brain happens from intensive 202 00:13:21,920 --> 00:13:24,680 Speaker 1: physical practice that you do, whether that's swimming or playing 203 00:13:24,720 --> 00:13:28,000 Speaker 1: the harmonica, or swinging a tennis racket or using a 204 00:13:28,120 --> 00:13:32,199 Speaker 1: rake or whatever. But these measurable brain changes, they don't 205 00:13:32,240 --> 00:13:35,079 Speaker 1: just apply to the physical they apply to the mental also, 206 00:13:35,480 --> 00:13:39,720 Speaker 1: so for example, when medical students study for their final 207 00:13:39,800 --> 00:13:43,480 Speaker 1: exams over the course of three months, particular areas of 208 00:13:43,520 --> 00:13:46,559 Speaker 1: their cortex changed so much that you can see this 209 00:13:46,720 --> 00:13:50,600 Speaker 1: on brain scans with the naked eye. And you see 210 00:13:50,640 --> 00:13:54,360 Speaker 1: something similar if you teach a person how to read 211 00:13:54,559 --> 00:13:59,680 Speaker 1: backward through a mirror. And here's another example. Areas of 212 00:13:59,679 --> 00:14:04,040 Speaker 1: the brain that are involved in spatial navigation are visibly 213 00:14:04,200 --> 00:14:08,439 Speaker 1: different in London taxi drivers from the rest of the population. 214 00:14:09,160 --> 00:14:13,280 Speaker 1: In each hemisphere, the taxi drivers have an enlarged region 215 00:14:13,360 --> 00:14:16,800 Speaker 1: part of the hippocampus, which is an area involved in 216 00:14:16,840 --> 00:14:38,600 Speaker 1: your internal maps of the outside world. So what you 217 00:14:38,680 --> 00:14:42,720 Speaker 1: spend your time on changes your brain. You are more 218 00:14:43,120 --> 00:14:47,280 Speaker 1: than what you eat. You become the information you digest. 219 00:14:47,680 --> 00:14:50,240 Speaker 1: And this is how the Polgar sisters were able to 220 00:14:50,320 --> 00:14:54,560 Speaker 1: blossom into world champion chess players. It's not because some 221 00:14:55,320 --> 00:14:59,120 Speaker 1: gene codes for skill at chess. It's because they practiced 222 00:14:59,280 --> 00:15:04,000 Speaker 1: over and over chiseling pathways in their brains to encode 223 00:15:04,080 --> 00:15:07,840 Speaker 1: the powers and patterns of knights and rooks and bishops 224 00:15:07,840 --> 00:15:11,480 Speaker 1: and ponds and kings and queens. So brains come to 225 00:15:11,960 --> 00:15:13,720 Speaker 1: reflect their world. 226 00:15:14,400 --> 00:15:17,680 Speaker 2: But how does this happen? Exactly. Well, let's see the. 227 00:15:17,640 --> 00:15:21,160 Speaker 1: Answer by zooming in on a weird illusion that most 228 00:15:21,160 --> 00:15:26,120 Speaker 1: of us have experienced, the phantom phone vibration. I recently 229 00:15:26,120 --> 00:15:28,320 Speaker 1: saw a meme online. It was a picture of a 230 00:15:28,400 --> 00:15:31,760 Speaker 1: human brain with the title that reads, Hey, I think 231 00:15:31,800 --> 00:15:34,200 Speaker 1: your phone just buzzed in your pocket, and then on 232 00:15:34,240 --> 00:15:37,400 Speaker 1: the bottom it reads, just kidding. Your phone isn't even 233 00:15:37,480 --> 00:15:41,800 Speaker 1: in your pocket, you moron. Now, the phantom cell phone 234 00:15:41,880 --> 00:15:45,560 Speaker 1: vibration is a menace that is unique to the twenty 235 00:15:45,560 --> 00:15:50,280 Speaker 1: first century. It happens because of a momentary spasm or 236 00:15:50,400 --> 00:15:53,480 Speaker 1: quivering or shaking, or a touch on your leg, And 237 00:15:53,560 --> 00:15:56,640 Speaker 1: as long as the frequency and the duration of that 238 00:15:56,720 --> 00:16:00,760 Speaker 1: feeling is vaguely similar to that made by your phone, 239 00:16:01,040 --> 00:16:04,760 Speaker 1: your brain decides on your behalf, that's something interesting is 240 00:16:04,760 --> 00:16:09,080 Speaker 1: happening with your phone. So thirty years ago, if you 241 00:16:09,160 --> 00:16:12,520 Speaker 1: had noticed a leg twitch, you would have interpreted the 242 00:16:12,560 --> 00:16:16,160 Speaker 1: feeling as a fly landing on you, or a movement 243 00:16:16,200 --> 00:16:21,160 Speaker 1: of your clothing, or something accidentally brushing past you. So 244 00:16:21,360 --> 00:16:25,480 Speaker 1: why does your interpretation differ from one generation to the next, 245 00:16:26,120 --> 00:16:31,320 Speaker 1: Because your phone now serves as the optimal explanation for 246 00:16:31,360 --> 00:16:35,560 Speaker 1: a whole range of twitchy feelings. So here's how to 247 00:16:35,600 --> 00:16:39,080 Speaker 1: understand what's happening there in the brain. Think of a 248 00:16:39,280 --> 00:16:45,080 Speaker 1: mountainous landscape. Now, picture a lake somewhere there that's encircled 249 00:16:45,080 --> 00:16:48,960 Speaker 1: by mountains. For a rain drop to end up in 250 00:16:48,960 --> 00:16:51,360 Speaker 1: that lake, it doesn't need to fall from the sky 251 00:16:51,560 --> 00:16:55,400 Speaker 1: and land directly in the water. Instead, it only needs 252 00:16:55,440 --> 00:16:59,280 Speaker 1: to hit the surrounding hillsides. It can land on the 253 00:16:59,320 --> 00:17:02,960 Speaker 1: northern slope or the southern, or the eastern incline or 254 00:17:03,000 --> 00:17:07,119 Speaker 1: the western and in any case it's gonna slide down into 255 00:17:07,240 --> 00:17:10,080 Speaker 1: the lake. So the lake is what's known as an 256 00:17:10,119 --> 00:17:15,520 Speaker 1: attractor state. Anything nearby will flow to that spot, and 257 00:17:15,600 --> 00:17:19,320 Speaker 1: you have lots of such attractor states in your brain. 258 00:17:19,920 --> 00:17:23,439 Speaker 1: So the feeling on your thigh doesn't have to be 259 00:17:23,600 --> 00:17:24,600 Speaker 1: a buzzing phone. 260 00:17:24,640 --> 00:17:26,760 Speaker 2: It can be a slight shift. 261 00:17:26,400 --> 00:17:29,159 Speaker 1: Of your genes or a twitch of your thigh muscle, 262 00:17:29,680 --> 00:17:33,000 Speaker 1: or an itch or graze past the sofa. 263 00:17:33,160 --> 00:17:37,359 Speaker 2: As long as the feeling is close, the signals. 264 00:17:37,080 --> 00:17:41,760 Speaker 1: Slide down the landscape to their attractor state, and then 265 00:17:41,800 --> 00:17:46,399 Speaker 1: you reach to check for an important message. The landscape 266 00:17:46,600 --> 00:17:51,879 Speaker 1: gets formed by what is important in your world. For 267 00:17:51,960 --> 00:17:55,560 Speaker 1: another example, think about the way we interpret the sounds 268 00:17:55,600 --> 00:17:58,400 Speaker 1: of language. It feels natural to you that you can 269 00:17:58,560 --> 00:18:03,040 Speaker 1: understand the sounds of your native language, but foreign languages 270 00:18:03,400 --> 00:18:06,359 Speaker 1: often have really close sounds that you can't hear the 271 00:18:06,400 --> 00:18:07,880 Speaker 1: difference between. 272 00:18:07,600 --> 00:18:11,560 Speaker 2: Like ooh and eh. But why why can you not 273 00:18:11,720 --> 00:18:12,280 Speaker 2: hear those? 274 00:18:13,040 --> 00:18:16,320 Speaker 1: As it turns out, there is something different about the 275 00:18:16,480 --> 00:18:20,480 Speaker 1: brains of the people who speak those languages. But they 276 00:18:20,520 --> 00:18:24,359 Speaker 1: weren't born that way, and neither were you. If you 277 00:18:24,400 --> 00:18:27,439 Speaker 1: look at the space of all the possible sounds that 278 00:18:27,520 --> 00:18:30,959 Speaker 1: humans can make with our mouths, it makes a relatively 279 00:18:31,080 --> 00:18:34,399 Speaker 1: smooth continuum. You can kind of make any sound. But 280 00:18:34,560 --> 00:18:39,360 Speaker 1: despite this, you learn from experience that specific sounds mean 281 00:18:39,440 --> 00:18:42,800 Speaker 1: the same thing, whether they're uttered by your dad, or 282 00:18:42,840 --> 00:18:47,159 Speaker 1: your babysitter or your teacher. Your brain figures out that 283 00:18:47,359 --> 00:18:52,280 Speaker 1: a drawn out E and eclip to e both belong 284 00:18:52,359 --> 00:18:55,679 Speaker 1: to the E category, or maybe your friend from Texas 285 00:18:55,680 --> 00:19:00,399 Speaker 1: says a or whatever. But your experience teaches you that 286 00:19:00,640 --> 00:19:04,600 Speaker 1: all the speakers mean the same sound, regardless of exactly 287 00:19:04,640 --> 00:19:08,080 Speaker 1: how they're pronouncing it, and so your neural networks carve 288 00:19:08,119 --> 00:19:12,160 Speaker 1: out a landscape in which all these sounds roll down 289 00:19:12,160 --> 00:19:16,840 Speaker 1: the hillsides to the same interpretation. There's a lake in 290 00:19:16,880 --> 00:19:20,560 Speaker 1: your brain that represents E, and all the inputs from 291 00:19:20,560 --> 00:19:25,120 Speaker 1: all around end up in that lake and in neighboring valleys, 292 00:19:25,160 --> 00:19:28,320 Speaker 1: you gather up sounds that are equivalent to A or 293 00:19:28,520 --> 00:19:32,920 Speaker 1: I or O and so on. So with time, your 294 00:19:33,080 --> 00:19:37,199 Speaker 1: landscape looks different from someone who's grown up in another 295 00:19:37,280 --> 00:19:41,800 Speaker 1: language and who needs to distinguish the smooth continuum of 296 00:19:41,920 --> 00:19:46,440 Speaker 1: sounds differently than you do. To think about an example 297 00:19:46,480 --> 00:19:50,880 Speaker 1: of this, imagine a baby born in Japan call him Hyato, 298 00:19:51,320 --> 00:19:55,280 Speaker 1: and a baby born in America call him William. From 299 00:19:55,320 --> 00:19:59,080 Speaker 1: their brain's point of view, there is nothing different about them. 300 00:19:59,720 --> 00:20:04,320 Speaker 1: But in Osaka, Hayato hears Japanese all around him. 301 00:20:04,320 --> 00:20:04,920 Speaker 2: From day one. 302 00:20:05,800 --> 00:20:10,320 Speaker 1: In Palo Alto, William hears the tones of English, where 303 00:20:10,400 --> 00:20:14,120 Speaker 1: different sounds carry meaning. An example of what these two 304 00:20:14,200 --> 00:20:17,000 Speaker 1: babies hear differently is the distinction between the. 305 00:20:17,400 --> 00:20:19,480 Speaker 2: R and L sounds. 306 00:20:19,920 --> 00:20:24,160 Speaker 1: So in English, these carry information like the word right 307 00:20:24,400 --> 00:20:29,480 Speaker 1: versus light or raw versus law, But in Japanese there's 308 00:20:29,520 --> 00:20:33,040 Speaker 1: no distinction between these two sounds. So as a result, 309 00:20:33,680 --> 00:20:39,359 Speaker 1: William's internal landscape builds a mountain range between his interpretation 310 00:20:39,640 --> 00:20:44,200 Speaker 1: of R and L, such that the difference between these 311 00:20:44,200 --> 00:20:50,040 Speaker 1: two sounds is perceptually clear. In Hyato's brain, the landscape 312 00:20:50,080 --> 00:20:53,480 Speaker 1: develops into a big valley, so that both R and 313 00:20:53,760 --> 00:20:57,320 Speaker 1: L flow into a single lake because they have an 314 00:20:57,400 --> 00:21:03,639 Speaker 1: identical interpretation. So as a result, Hyato can't hear the 315 00:21:03,760 --> 00:21:08,200 Speaker 1: difference between those two sounds. Now, obviously, the children's brains 316 00:21:08,200 --> 00:21:12,280 Speaker 1: were not born this way. Had William's pregnant mother moved 317 00:21:12,359 --> 00:21:16,119 Speaker 1: to Osaka and Hyato's pregnant mother to Palo Alto, the 318 00:21:16,119 --> 00:21:19,080 Speaker 1: boys would have had no trouble in becoming fluent speakers 319 00:21:19,119 --> 00:21:20,640 Speaker 1: and listeners in their new language. 320 00:21:21,240 --> 00:21:23,560 Speaker 2: As opposed to a genetic issue. 321 00:21:24,080 --> 00:21:29,359 Speaker 1: Their neural landscapes are carved by what is relevant in 322 00:21:29,400 --> 00:21:32,800 Speaker 1: their immediate environment. And what's fascinating is that you can 323 00:21:32,960 --> 00:21:37,520 Speaker 1: see this carving happening even before the children learn how 324 00:21:37,560 --> 00:21:42,320 Speaker 1: to speak. For example, make a continuous R sound and 325 00:21:42,359 --> 00:21:47,320 Speaker 1: then switch it over to L. So L, now, how 326 00:21:47,359 --> 00:21:51,680 Speaker 1: can you tell if an infant here's that change? 327 00:21:51,800 --> 00:21:53,680 Speaker 2: So it turns out the trick. 328 00:21:53,400 --> 00:21:57,560 Speaker 1: To the experiment is this, Infants will suck faster at 329 00:21:57,560 --> 00:22:00,640 Speaker 1: the nipple when they detect a chain. When they hear 330 00:22:00,640 --> 00:22:03,159 Speaker 1: a change from one sound to another sound, they go 331 00:22:03,240 --> 00:22:06,480 Speaker 1: from suck suck suck to suck suck, suck, suck. So 332 00:22:06,520 --> 00:22:10,560 Speaker 1: at the age of six months, both Hyato and William 333 00:22:11,240 --> 00:22:14,760 Speaker 1: will both suck faster when the R changes to L. 334 00:22:15,040 --> 00:22:20,840 Speaker 1: But by twelve months, Hyato stops detecting the change. R 335 00:22:20,920 --> 00:22:23,840 Speaker 1: and L sound the same to him. Both sounds are 336 00:22:24,000 --> 00:22:29,080 Speaker 1: sliding down into the same valley. Hyato's brain has lost 337 00:22:29,119 --> 00:22:33,200 Speaker 1: the ability to distinguish these sounds, while William's brain, having 338 00:22:33,560 --> 00:22:36,760 Speaker 1: passively listened to his parents speak tens of thousands of 339 00:22:36,800 --> 00:22:41,720 Speaker 1: English words, has learned that there's information carried in the 340 00:22:41,760 --> 00:22:45,960 Speaker 1: difference between these two sounds. Hyato's brain, meanwhile, has picked 341 00:22:46,040 --> 00:22:50,720 Speaker 1: up on other sound distinctions, which to William would be indistinguishable. 342 00:22:51,680 --> 00:22:57,720 Speaker 1: So your auditory system begins universally and then wires itself 343 00:22:57,760 --> 00:23:02,359 Speaker 1: to maximize the distinction unique to your language, depending on 344 00:23:02,720 --> 00:23:05,560 Speaker 1: where on the planet you happened to stick your head 345 00:23:05,600 --> 00:23:10,080 Speaker 1: out of the womb. And similarly, the buzzing phone isn't 346 00:23:10,119 --> 00:23:15,680 Speaker 1: something you were born to detect. Instead, it's high relevance 347 00:23:15,920 --> 00:23:19,639 Speaker 1: carves your neural landscape such that you have a broad 348 00:23:19,960 --> 00:23:23,080 Speaker 1: catch all for neighboring sensations, all of which you will 349 00:23:23,359 --> 00:23:27,520 Speaker 1: interpret as a buzzing cell phone in your pocket. Like kyata. 350 00:23:27,640 --> 00:23:30,760 Speaker 1: With the R and the L, you combine the twitches 351 00:23:30,800 --> 00:23:35,040 Speaker 1: and vibrations and quiverings into a single interpretation of what 352 00:23:35,359 --> 00:23:39,520 Speaker 1: just happened. Now, from what we've seen so far, we 353 00:23:39,600 --> 00:23:43,439 Speaker 1: might think that repetition is the key to molding the 354 00:23:43,480 --> 00:23:47,320 Speaker 1: circuitry in your brain. But in fact, there's a deeper 355 00:23:47,359 --> 00:23:51,680 Speaker 1: principle at work. So now we're going to talk about relevance. 356 00:23:52,119 --> 00:23:55,360 Speaker 1: There's an old joke that goes, how many psychiatrists does 357 00:23:55,400 --> 00:23:57,679 Speaker 1: it take to change a light bulb? And the answer 358 00:23:57,760 --> 00:24:01,160 Speaker 1: is only one, But the light bulb has to want 359 00:24:01,200 --> 00:24:05,000 Speaker 1: to change. Now, if you listen to episode two, you 360 00:24:05,040 --> 00:24:08,320 Speaker 1: may remember a dog that I talked about named Faith. 361 00:24:08,560 --> 00:24:12,359 Speaker 1: She is very memorable because Faith was born with out 362 00:24:12,359 --> 00:24:15,400 Speaker 1: front legs and she figured out how to walk by 363 00:24:15,560 --> 00:24:18,000 Speaker 1: pedaly on her hind legs, sort of like a human. 364 00:24:18,560 --> 00:24:18,840 Speaker 2: Now. 365 00:24:18,960 --> 00:24:21,920 Speaker 1: When I told her story in episode two, I said 366 00:24:21,920 --> 00:24:24,640 Speaker 1: it as though her brain had just figured out her 367 00:24:24,720 --> 00:24:27,920 Speaker 1: unusual body plan. But we can now dig a little 368 00:24:27,960 --> 00:24:32,520 Speaker 1: deeper for a hidden bone. Was there something special about Faith? 369 00:24:32,560 --> 00:24:35,439 Speaker 1: Could any dog have pulled us off? And if they 370 00:24:35,440 --> 00:24:37,399 Speaker 1: could have, why don't all dogs walk by? 371 00:24:37,480 --> 00:24:37,879 Speaker 2: Peeda Ly? 372 00:24:39,240 --> 00:24:44,280 Speaker 1: Faith's rewritten maps were all about relevance to her life. 373 00:24:44,760 --> 00:24:49,399 Speaker 1: Her brain was shaped by her goals. Faith needed to 374 00:24:49,440 --> 00:24:52,920 Speaker 1: get to her food. That required a solution. It wasn't 375 00:24:52,920 --> 00:24:54,959 Speaker 1: going to be the same one that was used by 376 00:24:55,000 --> 00:24:58,919 Speaker 1: her four legged siblings. She had to derive a novel solution, 377 00:24:59,560 --> 00:25:03,600 Speaker 1: so her brain tried out various strategies until it found 378 00:25:03,600 --> 00:25:07,119 Speaker 1: when that worked balancing on her two back legs and 379 00:25:07,200 --> 00:25:11,439 Speaker 1: lurching forward step after step. This allowed her to get 380 00:25:11,480 --> 00:25:14,520 Speaker 1: what she needed, and after a while, she became good 381 00:25:14,560 --> 00:25:18,840 Speaker 1: at this method of locomotion. In the absence of finding 382 00:25:18,880 --> 00:25:21,879 Speaker 1: an answer to her challenge, she would have starved and died. 383 00:25:22,680 --> 00:25:27,320 Speaker 1: Her drive for survival allowed the flexible circuitry in her 384 00:25:27,320 --> 00:25:31,119 Speaker 1: brain to try out a bunch of hypotheses and solve 385 00:25:31,480 --> 00:25:34,919 Speaker 1: the problem getting her to food and shelter and loved ones. 386 00:25:35,800 --> 00:25:37,359 Speaker 2: So goals matter. 387 00:25:37,880 --> 00:25:42,120 Speaker 1: A brain's goals play a critical role in how and 388 00:25:42,160 --> 00:25:47,200 Speaker 1: when it changes. For the Polgar sisters, achieving their expertise 389 00:25:47,280 --> 00:25:52,080 Speaker 1: depended on a desire to achieve their expertise. Same with 390 00:25:52,200 --> 00:25:56,760 Speaker 1: Yitzak Pearlman or Vladimir Ashkenazi. Imagine for a moment that 391 00:25:57,040 --> 00:26:01,919 Speaker 1: Serena and Venus Williams had a brother, Fred, and that 392 00:26:02,000 --> 00:26:04,720 Speaker 1: their parents had put a tennis racket in Fred's hands 393 00:26:04,720 --> 00:26:07,240 Speaker 1: and forced him to go through all the years of 394 00:26:07,359 --> 00:26:11,320 Speaker 1: practicing that his sisters went through. But imagine that he 395 00:26:11,480 --> 00:26:15,760 Speaker 1: found tennis repulsive. He never got good feedback from his 396 00:26:15,840 --> 00:26:19,960 Speaker 1: classmates about his performances, and he didn't win any contests, 397 00:26:20,440 --> 00:26:24,600 Speaker 1: and his elders didn't lavish him with praise. The result 398 00:26:24,680 --> 00:26:29,680 Speaker 1: of all that practice would be nothing. Fred's brain would 399 00:26:29,760 --> 00:26:34,159 Speaker 1: show little reorganization. Although his body was going through the 400 00:26:34,240 --> 00:26:39,160 Speaker 1: same motions as his sisters, the motions would be misaligned 401 00:26:39,200 --> 00:26:43,720 Speaker 1: with his internal incentives. So this is easily shown in 402 00:26:43,760 --> 00:26:47,080 Speaker 1: the laboratory. So imagine an experiment in which someone is 403 00:26:47,119 --> 00:26:50,920 Speaker 1: tapping out Morris code on your foot while someone else 404 00:26:51,000 --> 00:26:54,560 Speaker 1: totally separately is playing a sequence of sounds. 405 00:26:55,320 --> 00:26:56,040 Speaker 2: Now, if the. 406 00:26:56,040 --> 00:26:59,560 Speaker 1: Task is that you can win cash for decoding the 407 00:26:59,600 --> 00:27:03,640 Speaker 1: message on your foot, then the brain regions involved in 408 00:27:04,119 --> 00:27:08,240 Speaker 1: touch to that part of your body will develop higher resolution. 409 00:27:08,960 --> 00:27:12,400 Speaker 1: The regions involved in your hearing won't change, even though 410 00:27:12,440 --> 00:27:17,560 Speaker 1: that brain area is also receiving stimulation. Now imagine the 411 00:27:17,640 --> 00:27:22,280 Speaker 1: reverse game. Now, answering questions about subtle differences between the 412 00:27:22,359 --> 00:27:26,720 Speaker 1: sounds earns the cash while attending to your foot doesn't 413 00:27:26,800 --> 00:27:31,320 Speaker 1: yield anything. Now we'll see changes in the auditory cortex 414 00:27:31,400 --> 00:27:34,560 Speaker 1: where you're doing the hearing, but the touch in your 415 00:27:34,560 --> 00:27:39,160 Speaker 1: somatosensory cortex won't change. The inputs from the world are 416 00:27:39,200 --> 00:27:42,679 Speaker 1: exactly the same in both cases. But what changes in 417 00:27:42,720 --> 00:27:47,159 Speaker 1: your brain depends on what is rewarded. And this is 418 00:27:47,240 --> 00:27:51,280 Speaker 1: why Fred Williams gets no better on the tennis court. 419 00:27:51,359 --> 00:27:55,560 Speaker 1: He derives no reward from it. In his brain, just 420 00:27:55,600 --> 00:28:00,000 Speaker 1: like in yours, the maps of the neural territory reflect 421 00:28:00,119 --> 00:28:04,639 Speaker 1: to the strategies that have won positive feedback. Now this 422 00:28:04,760 --> 00:28:09,480 Speaker 1: kind of understanding about motivation and relevance leading to change 423 00:28:09,480 --> 00:28:14,240 Speaker 1: in the brain. This understanding opens new pathways for recovery 424 00:28:14,280 --> 00:28:17,600 Speaker 1: from brain damage. So imagine that a friend of yours 425 00:28:17,840 --> 00:28:21,119 Speaker 1: suffers a stroke. That damage is part of her motor cortex, 426 00:28:21,560 --> 00:28:25,680 Speaker 1: and as a result, one of her arms becomes mostly paralyzed. 427 00:28:26,440 --> 00:28:29,520 Speaker 1: So after trying many times to use her weakened arm, 428 00:28:29,920 --> 00:28:32,840 Speaker 1: she gets frustrated and just uses her good arm to 429 00:28:32,880 --> 00:28:37,280 Speaker 1: accomplish all the necessary tasks in her daily routine. This 430 00:28:37,359 --> 00:28:41,360 Speaker 1: is a typical scenario, and her weak arm becomes only 431 00:28:41,480 --> 00:28:45,600 Speaker 1: weaker because she's never choosing to use it. Now, the 432 00:28:45,720 --> 00:28:49,400 Speaker 1: lessons of brain plasticity that we've been talking about offer 433 00:28:49,560 --> 00:28:54,600 Speaker 1: a solution that is counterintuitive. The solution is known as 434 00:28:54,960 --> 00:28:59,880 Speaker 1: constraint therapy. You strap down her good arm so that 435 00:29:00,280 --> 00:29:03,640 Speaker 1: she can't use it, and that forces her to employ 436 00:29:03,760 --> 00:29:09,040 Speaker 1: the weak arm. Now, this simple method retrains the damaged 437 00:29:09,120 --> 00:29:13,400 Speaker 1: cortex by forcing use of the bad arm and cleverly 438 00:29:13,440 --> 00:29:18,840 Speaker 1: taking advantage of these neural mechanisms underlying desire and reward. 439 00:29:18,920 --> 00:29:23,120 Speaker 1: Because she has inherent motivation to get the sandwich to 440 00:29:23,200 --> 00:29:26,680 Speaker 1: her mouth, or to turn the key in her front door, 441 00:29:27,200 --> 00:29:30,360 Speaker 1: or to raise the cell phone to her ear, and 442 00:29:30,440 --> 00:29:34,960 Speaker 1: to perform all the other actions that underlie a dignified, 443 00:29:35,080 --> 00:29:40,480 Speaker 1: self sufficient life. So while constraint therapy starts off as frustrating, 444 00:29:41,160 --> 00:29:44,200 Speaker 1: the approach proves to be the best medicine because it 445 00:29:44,360 --> 00:29:49,120 Speaker 1: forces the brain to try new strategies, and the reward 446 00:29:49,720 --> 00:29:54,240 Speaker 1: locks in the methods that work. It seems paradoxical that 447 00:29:54,320 --> 00:29:56,760 Speaker 1: the solution of the problem is to make things worse, 448 00:29:57,360 --> 00:30:04,120 Speaker 1: but that's precisely what solves. So let's return to faith 449 00:30:04,320 --> 00:30:07,160 Speaker 1: the dog. Are all dogs able to walk on their 450 00:30:07,200 --> 00:30:11,560 Speaker 1: back legs? Sure, but most dogs will never have the 451 00:30:11,760 --> 00:30:15,360 Speaker 1: reason or motivation to attempt it, and certainly no reason 452 00:30:15,400 --> 00:30:19,320 Speaker 1: to master it. And that's why Faith became famous, not 453 00:30:19,400 --> 00:30:21,920 Speaker 1: because she's the only dog in the world who could 454 00:30:21,920 --> 00:30:24,320 Speaker 1: do it, but because she's the only one who made 455 00:30:24,320 --> 00:30:28,640 Speaker 1: it happen. You may know that some blind people learn 456 00:30:28,680 --> 00:30:32,120 Speaker 1: how to navigate using echolocation. They make sounds with their 457 00:30:32,160 --> 00:30:36,800 Speaker 1: mouth and they listen for the echo to give them information. 458 00:30:37,560 --> 00:30:41,360 Speaker 1: But it turns out that people with perfectly normal vision 459 00:30:41,880 --> 00:30:45,040 Speaker 1: can learn how to echo locate. Also, the issue is 460 00:30:45,160 --> 00:30:50,240 Speaker 1: just that most cited people simply are insufficiently motivated to 461 00:30:50,280 --> 00:30:56,200 Speaker 1: pour the hours and hours into redefining their neural territory. Now, 462 00:30:56,680 --> 00:31:00,920 Speaker 1: reward is a powerful way to rewire the brain, but happily, 463 00:31:01,000 --> 00:31:06,400 Speaker 1: your brain doesn't require cookies or cash. More generally, change 464 00:31:06,440 --> 00:31:10,200 Speaker 1: is tied to anything that's relevant to your goals. If 465 00:31:10,560 --> 00:31:12,360 Speaker 1: you're in the far North and you need to learn 466 00:31:12,360 --> 00:31:15,800 Speaker 1: about ice fishing and different types of snow, that's what 467 00:31:16,040 --> 00:31:20,400 Speaker 1: your brain will come to encode. If instead your equatorial 468 00:31:20,640 --> 00:31:23,040 Speaker 1: and you need to learn which snakes to avoid and 469 00:31:23,080 --> 00:31:28,480 Speaker 1: which mushrooms to eat, your brain will devote its resources accordingly. 470 00:31:29,560 --> 00:31:34,960 Speaker 1: Using relevance as it's north star, the brain flexibly picks 471 00:31:35,040 --> 00:31:39,680 Speaker 1: up on important details. It's billions of neurons serve as 472 00:31:39,720 --> 00:31:43,960 Speaker 1: a colossal canvas for painting the world that we happen 473 00:31:44,040 --> 00:31:48,000 Speaker 1: to find ourselves in, and with it we develop expertise 474 00:31:48,080 --> 00:31:51,960 Speaker 1: and whatever has relevance to us, whether that's basketball or 475 00:31:52,080 --> 00:31:56,560 Speaker 1: theater or badminton or Greek classics or cliff jumping or 476 00:31:56,680 --> 00:32:01,240 Speaker 1: video gaming or line dancing or wine making. Whenever a 477 00:32:01,360 --> 00:32:06,600 Speaker 1: task is roughly aligned with our larger goals, our brain. 478 00:32:06,400 --> 00:32:08,920 Speaker 2: Circuitry comes to reflect that. 479 00:32:10,000 --> 00:32:13,680 Speaker 1: Now, with how brains rewire based on what's relevant, I 480 00:32:13,760 --> 00:32:18,440 Speaker 1: realized really interesting analogy some years ago. Governments do the 481 00:32:18,520 --> 00:32:23,320 Speaker 1: same thing. They continually self design based on what's happening 482 00:32:23,440 --> 00:32:26,320 Speaker 1: in the nation. So just look at what happened. In 483 00:32:26,360 --> 00:32:29,400 Speaker 1: response to the attacks of September eleventh, two thousand and one, 484 00:32:30,040 --> 00:32:34,320 Speaker 1: the United States government altered its structure. It established the 485 00:32:34,360 --> 00:32:38,560 Speaker 1: Department of Homeland Security, which absorbed and restructured twenty two 486 00:32:38,600 --> 00:32:43,120 Speaker 1: existing agencies, And the same thing happened with the simmering 487 00:32:43,280 --> 00:32:47,000 Speaker 1: Cold War. This initiated a large shift in nineteen forty seven, 488 00:32:47,080 --> 00:32:51,840 Speaker 1: which spawned the Central Intelligence Agency, and in a thousand 489 00:32:51,920 --> 00:32:57,680 Speaker 1: small ways, a government subtly mirrors the current aims of 490 00:32:57,720 --> 00:33:00,640 Speaker 1: a nation and the events of its outside world. So 491 00:33:00,800 --> 00:33:06,000 Speaker 1: you have budgets swelling and shrinking to echo priorities when 492 00:33:06,120 --> 00:33:12,080 Speaker 1: external threats loom. The military pocketbook expands when peacetime follows. 493 00:33:12,520 --> 00:33:18,960 Speaker 1: Social initiatives gain. Just like brains, nations respond to changing 494 00:33:19,000 --> 00:33:25,520 Speaker 1: situations by shifting their resources and redrawing their organizational charts 495 00:33:25,800 --> 00:33:30,280 Speaker 1: to meet the challenges that they face. So how does 496 00:33:30,320 --> 00:33:33,680 Speaker 1: the brain know when something important has happened and that 497 00:33:33,800 --> 00:33:39,080 Speaker 1: it should change its wire accordingly. Well, one strategy is 498 00:33:39,120 --> 00:33:44,160 Speaker 1: to turn on plasticity when events in the world are correlated. 499 00:33:44,480 --> 00:33:47,200 Speaker 1: So the idea here is to just encode only those 500 00:33:47,240 --> 00:33:50,800 Speaker 1: things that co occur, Like you see a cow and 501 00:33:50,840 --> 00:33:55,440 Speaker 1: you hear a move, and in this way related events 502 00:33:55,480 --> 00:33:59,440 Speaker 1: become bound together in the brain tissue. Now, you generally 503 00:33:59,480 --> 00:34:03,640 Speaker 1: don't want to implement these changes too quickly, because sometimes 504 00:34:03,680 --> 00:34:06,480 Speaker 1: there are associations that are spurious. 505 00:34:06,520 --> 00:34:08,279 Speaker 2: You might see a cow. 506 00:34:08,160 --> 00:34:11,319 Speaker 1: But you hear the bark of an unrelated dog, and 507 00:34:11,480 --> 00:34:16,080 Speaker 1: you wouldn't want your brain to permanently store every accidental cooccurrence. 508 00:34:16,560 --> 00:34:20,360 Speaker 2: So the brain solution is to change slowly, just a 509 00:34:20,480 --> 00:34:21,799 Speaker 2: little at a time. 510 00:34:22,239 --> 00:34:25,080 Speaker 1: And in that way it comes to encode only those 511 00:34:25,160 --> 00:34:31,560 Speaker 1: things that commonly coincide real matches distinguish themselves from noise 512 00:34:31,600 --> 00:34:35,960 Speaker 1: by occurring together over and over and over. But despite 513 00:34:36,040 --> 00:34:41,000 Speaker 1: the wisdom of slow and steady change extracting averages like this, 514 00:34:41,200 --> 00:34:44,719 Speaker 1: that's not the whole story. Because just think about one 515 00:34:44,960 --> 00:34:47,839 Speaker 1: trial learning in which you, let's say, touch a hot 516 00:34:47,880 --> 00:34:50,440 Speaker 1: stove and you learn not to do that again. So 517 00:34:50,600 --> 00:34:54,919 Speaker 1: you've got emergency mechanisms that exist to make sure that 518 00:34:55,239 --> 00:35:00,319 Speaker 1: life threatening or limb threatening events are permanently retained. The 519 00:35:00,360 --> 00:35:03,920 Speaker 1: story of one trial learning goes deeper than that. Think 520 00:35:03,960 --> 00:35:06,200 Speaker 1: about when you were young and your aunt taught you 521 00:35:06,239 --> 00:35:11,080 Speaker 1: a new word. She says, this is called a pomegranate. Now, 522 00:35:11,239 --> 00:35:14,360 Speaker 1: you didn't need to learn that in an emergency situation, 523 00:35:14,920 --> 00:35:17,960 Speaker 1: and you didn't need your aunt to say this association 524 00:35:18,239 --> 00:35:22,400 Speaker 1: one hundred times. She calmly told you once, and you 525 00:35:22,480 --> 00:35:26,840 Speaker 1: got it in one trial. Why It's because it was 526 00:35:26,920 --> 00:35:30,680 Speaker 1: salient to you. You loved your aunt, and you derived 527 00:35:30,800 --> 00:35:33,440 Speaker 1: social benefit from knowing a new word and being able 528 00:35:33,480 --> 00:35:36,920 Speaker 1: to ask for the delicious fruit. This is one trial 529 00:35:37,000 --> 00:35:42,359 Speaker 1: learning not because of threat, but instead because of relevance. 530 00:35:43,440 --> 00:35:44,480 Speaker 2: Inside the brain. 531 00:35:45,000 --> 00:35:49,600 Speaker 1: This relevance is expressed through these widely reaching systems that 532 00:35:49,680 --> 00:35:56,120 Speaker 1: release chemicals called neuromodulators. By releasing these with high specificity, 533 00:35:56,280 --> 00:36:01,280 Speaker 1: these chemicals allow changes to occur only at specific places 534 00:36:01,280 --> 00:36:04,480 Speaker 1: and times instead of all over at every moment. An 535 00:36:04,600 --> 00:36:08,400 Speaker 1: especially important chemical messenger here is called acetylcholine. 536 00:36:09,239 --> 00:36:10,160 Speaker 2: Neurons that release the. 537 00:36:10,160 --> 00:36:14,520 Speaker 1: Seedlcholine are driven by both reward and punishment, and they're 538 00:36:14,600 --> 00:36:17,759 Speaker 1: active whenever you're learning a new task and need to 539 00:36:17,760 --> 00:36:21,200 Speaker 1: make changes, but they're not active once the task is 540 00:36:21,239 --> 00:36:22,080 Speaker 1: well established. 541 00:36:22,640 --> 00:36:23,680 Speaker 2: So here's what you need to know. 542 00:36:24,120 --> 00:36:28,360 Speaker 1: The presence of acetylcholine at a particular brain area tells 543 00:36:28,440 --> 00:36:30,920 Speaker 1: it to change, It doesn't tell it how to change. 544 00:36:31,480 --> 00:36:34,080 Speaker 1: In other words, when the neurons that spit out acetal 545 00:36:34,160 --> 00:36:39,320 Speaker 1: coline are active, they simply increase plasticity in the target areas. 546 00:36:39,680 --> 00:36:43,640 Speaker 1: When they are not active, there's little or no plasticity. 547 00:36:44,160 --> 00:36:47,400 Speaker 1: So here's an example. Imagine I play for you a 548 00:36:47,440 --> 00:36:57,760 Speaker 1: particular note on the piano, say D flat. The note 549 00:36:58,000 --> 00:37:01,760 Speaker 1: triggers activity in your auditory cortex, but it doesn't change 550 00:37:01,760 --> 00:37:05,200 Speaker 1: anything about how much territory is devoted to D flat. 551 00:37:05,680 --> 00:37:06,040 Speaker 2: Why not? 552 00:37:06,200 --> 00:37:10,200 Speaker 1: It's because the note doesn't mean anything in particular to you. Now, 553 00:37:10,320 --> 00:37:13,000 Speaker 1: let's say every time I play the note, I give 554 00:37:13,040 --> 00:37:17,440 Speaker 1: you a warm chocolate chip cookie. Now the note accrues 555 00:37:17,480 --> 00:37:23,040 Speaker 1: a meaning, and the brain territory devoted to D flat expands. 556 00:37:23,400 --> 00:37:27,880 Speaker 1: Your brain assigns more real estate to that frequency because 557 00:37:27,920 --> 00:37:33,560 Speaker 1: the presence of reward suggests it's important. Now, let's say 558 00:37:33,600 --> 00:37:37,280 Speaker 1: I don't have any cookies available, so instead of handing 559 00:37:37,320 --> 00:37:40,239 Speaker 1: you the treat, I play the D flat. At the 560 00:37:40,280 --> 00:37:43,640 Speaker 1: same moment that I stimulate neurons in your head that 561 00:37:43,680 --> 00:37:49,120 Speaker 1: release a setal colin. The cortical representation for that tone expands, 562 00:37:49,280 --> 00:37:52,440 Speaker 1: just like it did with the cookies. Your brain allocates 563 00:37:52,640 --> 00:37:56,600 Speaker 1: more terrain to that frequency because the presence of the 564 00:37:56,640 --> 00:38:01,160 Speaker 1: acetyl coline indicates that it must be important. So a 565 00:38:01,200 --> 00:38:05,440 Speaker 1: setyl colin broadcasts widely throughout the brain, and as a result, 566 00:38:05,480 --> 00:38:09,440 Speaker 1: it can trigger changes with whatever kind of relevant stimulus, 567 00:38:09,440 --> 00:38:13,280 Speaker 1: whether that's a musical note or a texture or something verbal. 568 00:38:13,800 --> 00:38:18,200 Speaker 1: It's a universal mechanism for saying this is important. Get 569 00:38:18,200 --> 00:38:24,000 Speaker 1: better at detecting this. It marks relevance by increasing territory, 570 00:38:24,480 --> 00:38:29,160 Speaker 1: and changes in neural territory map on to your performance. 571 00:38:30,160 --> 00:38:33,440 Speaker 1: So as an example of that, imagine that you have 572 00:38:33,480 --> 00:38:36,160 Speaker 1: to learn how to play some crazy new musical instrument. 573 00:38:36,640 --> 00:38:39,560 Speaker 1: So a couple of weeks of practice improves your speed 574 00:38:39,600 --> 00:38:43,800 Speaker 1: and your skill, and you have a correspondingly large increase 575 00:38:43,880 --> 00:38:47,600 Speaker 1: in the brain areas that are involved. But if you 576 00:38:47,640 --> 00:38:50,680 Speaker 1: are a seedyl colin release is blocked with a drug, 577 00:38:51,200 --> 00:38:55,399 Speaker 1: those brain areas don't grow and your skill never improves. 578 00:38:56,320 --> 00:39:00,160 Speaker 1: So the basis of the behavioral improvement is not simply 579 00:39:00,200 --> 00:39:04,960 Speaker 1: the repeated performance of the task. It requires these neuromodulatory 580 00:39:05,040 --> 00:39:10,759 Speaker 1: systems to encode relevance. Without the acetyl coline, the ten 581 00:39:10,840 --> 00:39:16,520 Speaker 1: thousand hours is wasted time. So with the hypothetical Fred Williams, 582 00:39:16,520 --> 00:39:20,040 Speaker 1: who hates tennis, why didn't his brain change even after 583 00:39:20,080 --> 00:39:23,520 Speaker 1: the same number of hours of practice as his sisters. 584 00:39:24,120 --> 00:39:29,120 Speaker 1: It's because these neuromodulatory systems were not engaged in his 585 00:39:29,239 --> 00:39:33,680 Speaker 1: head as he drilled backhands over and over. He's like 586 00:39:33,760 --> 00:39:36,360 Speaker 1: you practicing the instrument with no acetal colin. 587 00:39:37,120 --> 00:39:39,359 Speaker 2: As a quick side note, these acetal. 588 00:39:39,080 --> 00:39:42,680 Speaker 1: Colin neurons reach out widely across the brain. So when 589 00:39:42,680 --> 00:39:46,560 Speaker 1: these start chattering away, why doesn't that turn on plasticity 590 00:39:47,000 --> 00:39:52,120 Speaker 1: everywhere they reach, causing widespread neural changes. The answer is 591 00:39:52,160 --> 00:39:57,240 Speaker 1: that acetyl coline's release and its effects are modulated. 592 00:39:56,640 --> 00:39:58,280 Speaker 2: By other neural modulators. 593 00:39:58,719 --> 00:40:03,560 Speaker 1: So while acetal colon turns on plasticity, other neurotransmitters like 594 00:40:03,600 --> 00:40:07,279 Speaker 1: dopamine are involved in the direction of change, encoding whether 595 00:40:07,400 --> 00:40:11,600 Speaker 1: something was punishing or rewarding. Researchers all over the planet 596 00:40:11,680 --> 00:40:16,120 Speaker 1: are still working to decipher this very complex choreography of 597 00:40:16,160 --> 00:40:20,080 Speaker 1: the neurotransmitter systems. But what we know is that collectively, 598 00:40:20,560 --> 00:40:26,000 Speaker 1: these chemical messengers allow reconfiguration in some areas while keeping 599 00:40:26,000 --> 00:40:27,640 Speaker 1: the rest locked down. 600 00:40:28,800 --> 00:40:31,760 Speaker 2: So let's go back to the London taxi drivers. 601 00:40:32,120 --> 00:40:35,279 Speaker 1: They're famous for having to memorize the entire map of 602 00:40:35,360 --> 00:40:38,520 Speaker 1: the streets of London, and they train for months and 603 00:40:38,640 --> 00:40:41,359 Speaker 1: months on this task, and I mentioned before there are 604 00:40:41,520 --> 00:40:45,080 Speaker 1: physical changes in the structure of their brain as a result. 605 00:40:45,560 --> 00:40:48,400 Speaker 1: These cavies are able to pull off this staggering feet 606 00:40:49,280 --> 00:40:52,839 Speaker 1: because the map is relevant to them. This is their 607 00:40:53,320 --> 00:40:56,760 Speaker 1: desired employment, which is going to pay for their home mortgage, 608 00:40:56,840 --> 00:41:01,960 Speaker 1: or their child's tuition, or their upcoming marriage. But interestingly, 609 00:41:02,080 --> 00:41:05,279 Speaker 1: since the study of the cabbys was first published in 610 00:41:05,440 --> 00:41:08,920 Speaker 1: the year two thousand, the need for this kind of 611 00:41:08,960 --> 00:41:12,640 Speaker 1: memorization has essentially gone away. Now it's just as easy 612 00:41:12,680 --> 00:41:15,680 Speaker 1: to have Google memorize all the streets of London, and 613 00:41:15,719 --> 00:41:19,120 Speaker 1: more generally, all the streets interlacing the planet. So the 614 00:41:19,320 --> 00:41:21,919 Speaker 1: kind of brain changes that we saw at the turn 615 00:41:21,960 --> 00:41:24,280 Speaker 1: of the century, we probably. 616 00:41:23,840 --> 00:41:25,680 Speaker 2: Won't be seeing in them anymore. 617 00:41:26,560 --> 00:41:31,160 Speaker 1: What's interesting is that AI algorithms don't care about relevance. 618 00:41:31,200 --> 00:41:33,759 Speaker 1: They memorize whatever we ask them to, which is a 619 00:41:33,840 --> 00:41:37,440 Speaker 1: super useful feature of AI, but it's also the reason 620 00:41:37,480 --> 00:41:41,560 Speaker 1: that AI is not exactly human like, because AI just 621 00:41:41,560 --> 00:41:44,840 Speaker 1: doesn't care which problems are interesting or germane. It just 622 00:41:45,040 --> 00:41:49,279 Speaker 1: memorizes whatever we feed it, So whether that's distinguishing a 623 00:41:49,320 --> 00:41:52,760 Speaker 1: horse from a zebra in a billion photographs or tracking 624 00:41:52,800 --> 00:41:55,960 Speaker 1: flight data from every airport on the planet, it has 625 00:41:56,000 --> 00:42:01,160 Speaker 1: no sense of importance except in a statistical sense. Contemporary 626 00:42:01,200 --> 00:42:06,320 Speaker 1: AI could never by itself decide that it finds irresistible 627 00:42:06,360 --> 00:42:10,520 Speaker 1: a particular sculpture by Michaelangelo, or that it hates the 628 00:42:10,560 --> 00:42:14,840 Speaker 1: taste of bitter tea, or that it's aroused by signals 629 00:42:14,840 --> 00:42:19,120 Speaker 1: of fertility. AI can dispatch ten thousand hours of intense 630 00:42:19,160 --> 00:42:23,520 Speaker 1: practice in ten thousand nanoseconds, but it doesn't favor any 631 00:42:23,760 --> 00:42:27,040 Speaker 1: zeros and ones over others. As a result, AI can 632 00:42:27,080 --> 00:42:31,719 Speaker 1: accomplish super impressive feats, but not yet the feat of 633 00:42:31,760 --> 00:42:35,240 Speaker 1: being anything like a human who cares about some things 634 00:42:35,760 --> 00:42:59,239 Speaker 1: more than others. Now, how does the modifiability of the 635 00:42:59,320 --> 00:43:03,640 Speaker 1: brain and its relationship to relevance bear on the way 636 00:43:03,719 --> 00:43:08,239 Speaker 1: that we teach our young The traditional classroom consists of 637 00:43:08,360 --> 00:43:12,840 Speaker 1: a teacher that's droning on, possibly reading from bulleted slides. 638 00:43:13,239 --> 00:43:17,560 Speaker 1: This is totally suboptimal for brain changes because the students 639 00:43:17,600 --> 00:43:22,560 Speaker 1: aren't engaged, and without engagement there's little or no plasticity. 640 00:43:22,600 --> 00:43:27,320 Speaker 1: The information doesn't stick. Now, we are not the first 641 00:43:27,320 --> 00:43:30,879 Speaker 1: generation to make this observation. The ancient Greeks had noted this. 642 00:43:31,400 --> 00:43:33,759 Speaker 1: They didn't have the tools of modern neuroscience, but they 643 00:43:33,760 --> 00:43:37,880 Speaker 1: had a sharp eye, and they defined seven different levels 644 00:43:37,920 --> 00:43:41,719 Speaker 1: of learning, and the highest level where the best learning occurs, 645 00:43:42,440 --> 00:43:47,799 Speaker 1: is achieved when a student is invested and curious and interested. 646 00:43:48,760 --> 00:43:51,839 Speaker 1: Through a modern lens, we would say that a particular 647 00:43:51,960 --> 00:43:56,240 Speaker 1: formula of neurotransmitters is required for neural changes to take place, 648 00:43:56,560 --> 00:44:02,000 Speaker 1: and that formula correlates with investment and curiosity and interest 649 00:44:02,640 --> 00:44:06,880 Speaker 1: this trick of inspiring curiosity. This is woven into several 650 00:44:06,960 --> 00:44:11,920 Speaker 1: traditional forms of learning. So, for example, Jewish religious scholars 651 00:44:12,000 --> 00:44:16,400 Speaker 1: will study the Talmud by sitting in pairs and posing 652 00:44:16,440 --> 00:44:20,000 Speaker 1: interesting questions to each other, like why does the author 653 00:44:20,120 --> 00:44:22,799 Speaker 1: use this particular word instead of a different word? Or 654 00:44:23,320 --> 00:44:26,600 Speaker 1: why do these two authorities differ in their account? Everything 655 00:44:26,640 --> 00:44:30,520 Speaker 1: gets cast as a question, which forces their learning partner 656 00:44:30,560 --> 00:44:33,719 Speaker 1: to engage instead of memorize. And although this is an 657 00:44:33,760 --> 00:44:37,560 Speaker 1: ancient study structure, I recently stumbled on a website that 658 00:44:37,640 --> 00:44:44,920 Speaker 1: poses talmudic questions about microbial biology. Questions like, given that 659 00:44:45,120 --> 00:44:50,279 Speaker 1: spores are so effective in ensuring survival of bacteria, why 660 00:44:50,320 --> 00:44:54,239 Speaker 1: don't all species make them? Or do we know for 661 00:44:54,400 --> 00:44:58,000 Speaker 1: sure that there are only three domains of life bacteria, 662 00:44:58,120 --> 00:45:03,440 Speaker 1: Archaea and Eucaria, Or how come peptides made enzematically don't 663 00:45:03,440 --> 00:45:07,480 Speaker 1: seem to get strung together to make a respectably sized protein. 664 00:45:08,320 --> 00:45:10,080 Speaker 2: This site has hundreds. 665 00:45:09,680 --> 00:45:14,000 Speaker 1: Of questions like this, which coaxes an active engagement in 666 00:45:14,040 --> 00:45:18,320 Speaker 1: its readers instead of simply telling them answers and more generally, 667 00:45:18,360 --> 00:45:21,080 Speaker 1: this is why joining a study group always helps. It 668 00:45:21,120 --> 00:45:23,600 Speaker 1: doesn't matter if you're studying calculus or history or whatever. 669 00:45:23,960 --> 00:45:30,360 Speaker 1: A study group activates the brain's social mechanisms to motivate engagement. 670 00:45:31,560 --> 00:45:31,880 Speaker 2: Now. 671 00:45:31,960 --> 00:45:35,200 Speaker 1: I saw a wonderful interview in the nineteen eighties where 672 00:45:35,239 --> 00:45:39,280 Speaker 1: the author Isaac Asimov gave an interview with the television 673 00:45:39,320 --> 00:45:43,600 Speaker 1: journalist Bill Moyers, and Asimov saw the limits of the 674 00:45:43,640 --> 00:45:46,560 Speaker 1: traditional education system with really clear eyes. And here's what 675 00:45:46,600 --> 00:45:50,360 Speaker 1: he said. He said, quote, today, what people call learning 676 00:45:50,719 --> 00:45:52,960 Speaker 1: is forced on you. Everyone is forced to learn the 677 00:45:53,000 --> 00:45:55,760 Speaker 1: same thing on the same day, at the same speed 678 00:45:55,760 --> 00:45:59,799 Speaker 1: in class. But everyone is different. For some, class goes 679 00:45:59,840 --> 00:46:02,279 Speaker 1: to fast, for some, it goes too slow, for some 680 00:46:02,400 --> 00:46:08,440 Speaker 1: in the wrong direction. Asimov had a vision for individualized education, 681 00:46:08,640 --> 00:46:11,839 Speaker 1: although he couldn't see the details. He was squinting into 682 00:46:11,880 --> 00:46:16,520 Speaker 1: the future, and he anticipated the Internet. He said, quote, 683 00:46:17,120 --> 00:46:20,239 Speaker 1: give everyone a chance to follow up their own bent 684 00:46:20,400 --> 00:46:23,800 Speaker 1: from the start, to find out about whatever they're interested 685 00:46:23,840 --> 00:46:26,480 Speaker 1: in by looking it up in their own homes, at 686 00:46:26,480 --> 00:46:30,240 Speaker 1: their own speed, in their own time, and everyone will 687 00:46:30,400 --> 00:46:31,800 Speaker 1: enjoy learning. 688 00:46:32,840 --> 00:46:33,360 Speaker 2: End quote. 689 00:46:34,320 --> 00:46:37,759 Speaker 1: It's through this lens of triggering interest that a lot 690 00:46:37,760 --> 00:46:40,839 Speaker 1: of philanthropists like Bill and Melinda Gates are aiming to 691 00:46:41,000 --> 00:46:46,279 Speaker 1: build adaptive learning. The idea is you leverage software that 692 00:46:46,440 --> 00:46:49,680 Speaker 1: quickly determines the state of knowledge of each student, and 693 00:46:49,719 --> 00:46:52,520 Speaker 1: then instructs each student on exactly what he or she 694 00:46:52,600 --> 00:46:55,600 Speaker 1: needs to know next. It's like having a one to 695 00:46:55,719 --> 00:47:00,200 Speaker 1: one student teacher ratio. This approach keeps each student the 696 00:47:00,280 --> 00:47:03,279 Speaker 1: right pace, meeting him where he is right now, with 697 00:47:03,360 --> 00:47:08,200 Speaker 1: the material that will captivate and This past May, Saul 698 00:47:08,320 --> 00:47:10,600 Speaker 1: Kahn gave a great talk at TED where he talked 699 00:47:10,600 --> 00:47:16,160 Speaker 1: about using AI to personalize learning. With AI, the students 700 00:47:16,160 --> 00:47:18,280 Speaker 1: can learn at their own pace and in their own way, 701 00:47:18,560 --> 00:47:22,279 Speaker 1: and he's increasingly making con Academy as a way to 702 00:47:22,360 --> 00:47:27,280 Speaker 1: show how AI can create totally personalized learning experiences based 703 00:47:27,320 --> 00:47:32,839 Speaker 1: on that student's individual strengths and weaknesses, like asm Off 704 00:47:32,880 --> 00:47:35,759 Speaker 1: and Gates and con and many others. I am a 705 00:47:36,000 --> 00:47:39,959 Speaker 1: cyber optimist on the topic of education. I always find 706 00:47:40,000 --> 00:47:43,560 Speaker 1: myself on Wikipedia, where I'm just following my interest. I 707 00:47:43,920 --> 00:47:46,239 Speaker 1: click on one link and I'm reading, and then I think, WHOA, 708 00:47:46,239 --> 00:47:49,120 Speaker 1: what's that? And I follow that link and after about 709 00:47:49,280 --> 00:47:52,560 Speaker 1: twelve links, I'm down some mole hole and I think, Wow, 710 00:47:52,680 --> 00:47:55,960 Speaker 1: how did I get from that topic over here? I 711 00:47:56,040 --> 00:47:59,560 Speaker 1: think that drilling down through these blind mole holes of 712 00:47:59,560 --> 00:48:04,080 Speaker 1: wikiped without any pre specified plan may turn out to 713 00:48:04,160 --> 00:48:08,600 Speaker 1: be a near optimal way to learn and more generally, 714 00:48:08,640 --> 00:48:12,040 Speaker 1: what the Internet allows is for students and all of 715 00:48:12,120 --> 00:48:15,560 Speaker 1: us to answer questions as soon. 716 00:48:15,400 --> 00:48:16,760 Speaker 2: As they pop into our heads. 717 00:48:17,520 --> 00:48:20,840 Speaker 1: We get the answer in the context of our curiosity. 718 00:48:21,719 --> 00:48:24,160 Speaker 1: And this is the powerful difference between the way that 719 00:48:24,200 --> 00:48:27,400 Speaker 1: many of us grew up with just in case information, 720 00:48:28,160 --> 00:48:30,440 Speaker 1: like just in case you need to know it the 721 00:48:30,440 --> 00:48:34,359 Speaker 1: Battle of Hastings occurred in ten sixty six, and what's 722 00:48:34,400 --> 00:48:39,000 Speaker 1: happening now, which is just in time information, which is 723 00:48:39,400 --> 00:48:42,400 Speaker 1: getting the information the moment that you seek the answer. 724 00:48:43,560 --> 00:48:46,399 Speaker 1: Generally speaking, it's only in the latter case, when you're 725 00:48:46,400 --> 00:48:49,879 Speaker 1: doing just in time information that you find the right 726 00:48:50,040 --> 00:48:52,280 Speaker 1: brew of neuromodulators present. 727 00:48:53,680 --> 00:48:54,600 Speaker 2: The Chinese have. 728 00:48:54,560 --> 00:48:58,480 Speaker 1: An expression an hour with a wise person is worth 729 00:48:58,600 --> 00:49:02,440 Speaker 1: more than one thousand busos, and this insight is the 730 00:49:02,680 --> 00:49:05,520 Speaker 1: ancient equivalent of what the Internet offers. 731 00:49:06,200 --> 00:49:08,760 Speaker 2: When the learner can actively direct her. 732 00:49:08,640 --> 00:49:13,160 Speaker 1: Own learning by asking the wise person precisely the question 733 00:49:13,239 --> 00:49:17,719 Speaker 1: that she wants to answer, the molecules of relevance and 734 00:49:17,800 --> 00:49:19,320 Speaker 1: reward are present. 735 00:49:19,400 --> 00:49:22,320 Speaker 2: They allow the brain to reconfigure. 736 00:49:22,760 --> 00:49:26,319 Speaker 1: When you toss facts and an unengaged student, it's like 737 00:49:26,360 --> 00:49:30,120 Speaker 1: throwing pebbles to dent a stone wall. It's like trying 738 00:49:30,160 --> 00:49:34,440 Speaker 1: to get Fred Williams to absorb tennis. So in this 739 00:49:34,560 --> 00:49:39,960 Speaker 1: light we have great opportunities because of the gamification of education. 740 00:49:40,480 --> 00:49:45,560 Speaker 1: You have this adaptive software which keeps students working at 741 00:49:45,600 --> 00:49:48,960 Speaker 1: their point of struggle, where finding the right answer is 742 00:49:49,480 --> 00:49:53,520 Speaker 1: frustrating but achievable. If the student can't get the answer, 743 00:49:53,560 --> 00:49:56,479 Speaker 1: the questions stay at the same level. When he gets 744 00:49:56,560 --> 00:49:59,359 Speaker 1: the right answer, the questions get harder. So there's still 745 00:49:59,360 --> 00:50:03,000 Speaker 1: a role for the teacher here to teach foundational concepts 746 00:50:03,000 --> 00:50:07,320 Speaker 1: and to guide the path of learning. But fundamentally, given 747 00:50:07,360 --> 00:50:13,080 Speaker 1: how brains adapt and rewrite their wiring, a neuroscience compatible 748 00:50:13,120 --> 00:50:16,840 Speaker 1: classroom is one in which the students drill into the 749 00:50:16,960 --> 00:50:21,960 Speaker 1: vast sphere of human knowledge by following the paths of 750 00:50:22,040 --> 00:50:28,880 Speaker 1: their individual passions. So the future of education looks very favorable. 751 00:50:29,360 --> 00:50:31,520 Speaker 1: But one question remains, and I just want to address 752 00:50:31,560 --> 00:50:34,880 Speaker 1: this here because I get asked this so often. Given 753 00:50:34,920 --> 00:50:38,799 Speaker 1: that the brain becomes wired from experience, what are the 754 00:50:38,920 --> 00:50:43,279 Speaker 1: neural consequences of growing up on screens? Are the brains 755 00:50:43,440 --> 00:50:47,080 Speaker 1: of digital natives different from the brains of the generations 756 00:50:47,120 --> 00:50:50,520 Speaker 1: before them. Now, it comes as a surprise to many 757 00:50:50,560 --> 00:50:53,520 Speaker 1: people that there aren't more studies on this than neuroscience. 758 00:50:53,840 --> 00:50:57,640 Speaker 1: Wouldn't our society want to understand the differences between the 759 00:50:57,800 --> 00:51:00,280 Speaker 1: digital and analog raised brain. 760 00:51:01,320 --> 00:51:04,279 Speaker 2: Yes, we would. But the reason there are no. 761 00:51:04,320 --> 00:51:09,319 Speaker 1: Good studies on this is because it's inordinately difficult to 762 00:51:09,440 --> 00:51:14,560 Speaker 1: perform meaningful science on this. Why because there's no good 763 00:51:14,680 --> 00:51:20,280 Speaker 1: control group against which to compare a digital native's brain. 764 00:51:20,760 --> 00:51:24,800 Speaker 1: You can't easily find another group of eighteen year olds 765 00:51:25,040 --> 00:51:27,840 Speaker 1: who haven't grown up with the Internet. You might find 766 00:51:28,120 --> 00:51:32,719 Speaker 1: some Amish teenagers in Pennsylvania, but there are dozens of 767 00:51:32,880 --> 00:51:36,600 Speaker 1: other differences with that group, such as religious and cultural 768 00:51:36,600 --> 00:51:40,440 Speaker 1: and educational beliefs. Where else could you find young people 769 00:51:40,480 --> 00:51:43,680 Speaker 1: of the same age who grew up without access to 770 00:51:43,719 --> 00:51:45,920 Speaker 1: the Internet. You might be able to turn up some 771 00:51:46,520 --> 00:51:50,880 Speaker 1: impoverished children in rural China, or in a village in 772 00:51:51,000 --> 00:51:54,239 Speaker 1: Central America or in the Kalahari Desert, but there are 773 00:51:54,280 --> 00:51:57,440 Speaker 1: going to be other major differences with those children and 774 00:51:57,520 --> 00:52:01,760 Speaker 1: the digital natives whom you intended to understand, including wealth 775 00:52:01,760 --> 00:52:07,640 Speaker 1: and education and diet, So it's not a useful control group. Okay, 776 00:52:07,680 --> 00:52:11,680 Speaker 1: So maybe you could compare millennials against the generation that 777 00:52:11,760 --> 00:52:15,480 Speaker 1: came before them, like their parents, who didn't grow up online, 778 00:52:15,680 --> 00:52:19,279 Speaker 1: but who instead played street stickball and stuffed twinkies in 779 00:52:19,320 --> 00:52:22,080 Speaker 1: their mouths as they watched The Brady Bunch. But this 780 00:52:22,200 --> 00:52:27,640 Speaker 1: is also problematic because between two generations there are innumerable 781 00:52:27,680 --> 00:52:32,280 Speaker 1: differences of politics and nutrition and pollution and cultural innovation, 782 00:52:33,280 --> 00:52:36,160 Speaker 1: such that if you find differences in the brain, you 783 00:52:36,200 --> 00:52:37,160 Speaker 1: have no idea what to. 784 00:52:37,160 --> 00:52:38,080 Speaker 2: Attribute it to. 785 00:52:39,080 --> 00:52:42,719 Speaker 1: So this is an intractable problem to pull off a 786 00:52:42,760 --> 00:52:45,920 Speaker 1: well controlled experiment about the effect of growing up with 787 00:52:45,960 --> 00:52:50,080 Speaker 1: the Internet. Nonetheless, I can tell you the root of 788 00:52:50,120 --> 00:52:54,480 Speaker 1: my optimism about this. Never before have we had the 789 00:52:54,760 --> 00:52:59,280 Speaker 1: entirety of humankind's knowledge in a rectangle in our pockets, 790 00:52:59,600 --> 00:53:03,560 Speaker 1: with constant and immediate access. Some of you will remember 791 00:53:03,640 --> 00:53:06,719 Speaker 1: taking trips down to the library and you look around 792 00:53:06,800 --> 00:53:10,120 Speaker 1: for the Encyclopedia Britannica, and you find the letter and 793 00:53:10,200 --> 00:53:13,040 Speaker 1: you hope there's an article there about what you're looking for, 794 00:53:13,120 --> 00:53:15,880 Speaker 1: and if it's there, you hope that it's not too 795 00:53:15,960 --> 00:53:19,160 Speaker 1: many decades old and that the information is still relevant. 796 00:53:19,520 --> 00:53:21,880 Speaker 1: And if you can find an article there, then you 797 00:53:21,920 --> 00:53:24,120 Speaker 1: have to go to the card catalog and you flip 798 00:53:24,160 --> 00:53:26,960 Speaker 1: through it and hope that there's a book somewhere in 799 00:53:27,000 --> 00:53:30,640 Speaker 1: the library that addresses what you want to know in 800 00:53:30,680 --> 00:53:35,319 Speaker 1: a surprisingly brief period. This is all changed, and as 801 00:53:35,360 --> 00:53:39,600 Speaker 1: a result, we've all seen the transition of dinner time debates, 802 00:53:39,680 --> 00:53:44,239 Speaker 1: where the winner has transitioned from being the loudest or 803 00:53:44,280 --> 00:53:47,120 Speaker 1: most pervasive to the person who can whip out the 804 00:53:47,160 --> 00:53:51,200 Speaker 1: phone the fastest and google the fact in question. Discussions 805 00:53:51,280 --> 00:53:54,720 Speaker 1: move really rapidly now, they leap from one solved question 806 00:53:54,800 --> 00:53:57,640 Speaker 1: to the next, and even when we're by ourselves, there's 807 00:53:57,840 --> 00:53:58,200 Speaker 1: just no. 808 00:53:58,360 --> 00:54:01,680 Speaker 2: End to the learning that goes on. When we look up. 809 00:54:01,640 --> 00:54:04,439 Speaker 1: The Wikipedia page, which cascades is down the next link 810 00:54:04,480 --> 00:54:08,080 Speaker 1: in the next such that six jumps later, we're learning 811 00:54:08,120 --> 00:54:09,960 Speaker 1: facts that we didn't even know we didn't know. 812 00:54:10,560 --> 00:54:14,800 Speaker 2: And the great advantage of this comes from a simple fact. 813 00:54:14,960 --> 00:54:18,200 Speaker 1: All new ideas in your brain come from a mashup 814 00:54:18,320 --> 00:54:22,799 Speaker 1: of previously learned inputs, and today we get more new 815 00:54:22,920 --> 00:54:26,919 Speaker 1: inputs than ever before. And so our children are living 816 00:54:27,000 --> 00:54:33,439 Speaker 1: in a time unparalleled in richness. Our knowledge sphere has 817 00:54:33,520 --> 00:54:37,719 Speaker 1: exploded in diameter, and as it grows, it offers more 818 00:54:37,880 --> 00:54:42,719 Speaker 1: doors for entry. So young minds have the opportunity to 819 00:54:42,880 --> 00:54:48,160 Speaker 1: cross link facts from completely different domains to generate ideas 820 00:54:48,239 --> 00:54:51,840 Speaker 1: that previous eras couldn't even have imagined, and this partially 821 00:54:51,880 --> 00:54:56,600 Speaker 1: explains the exponential increase in human scholarship. We have faster 822 00:54:56,680 --> 00:55:01,360 Speaker 1: communication and more mashups than ever before. So it's not 823 00:55:01,480 --> 00:55:04,440 Speaker 1: clear what all the social and political consequences of the 824 00:55:04,480 --> 00:55:08,839 Speaker 1: Internet will be, but from a neuroscience perspective, it unlocks 825 00:55:09,000 --> 00:55:15,280 Speaker 1: a much richer level of education. So in earlier podcasts 826 00:55:15,320 --> 00:55:18,840 Speaker 1: we looked at brain changes resulting from changes to the 827 00:55:18,880 --> 00:55:22,320 Speaker 1: body plan in terms of either new sensors or new limbs, 828 00:55:22,600 --> 00:55:25,160 Speaker 1: and in this episode we turn to changes that result 829 00:55:25,239 --> 00:55:30,359 Speaker 1: from practiced motor acts or rewarding sensory inputs. But the 830 00:55:30,520 --> 00:55:35,520 Speaker 1: larger principle that ties all these scenarios together is relevance. 831 00:55:35,719 --> 00:55:39,799 Speaker 1: Your brain adjusts itself according to what you spend your 832 00:55:39,840 --> 00:55:42,960 Speaker 1: time on as long as those tasks have alignment with 833 00:55:43,520 --> 00:55:47,560 Speaker 1: rewards or your goals. For a person who goes blind, 834 00:55:48,160 --> 00:55:52,799 Speaker 1: expanding the other senses takes on a heightened relevance, and 835 00:55:52,840 --> 00:55:56,360 Speaker 1: this is the deeper origin behind the changes that allow 836 00:55:56,440 --> 00:56:00,720 Speaker 1: her visual cortex to get taken over. If a person 837 00:56:01,080 --> 00:56:04,960 Speaker 1: passes her fingers repeatedly over the bumps of braille but 838 00:56:05,120 --> 00:56:08,919 Speaker 1: has no motivation to learn it then no rewiring takes 839 00:56:08,960 --> 00:56:10,840 Speaker 1: place because the right. 840 00:56:10,760 --> 00:56:13,120 Speaker 2: Neuromodulators just aren't present. 841 00:56:14,000 --> 00:56:16,080 Speaker 1: And in the same way, if you add a new 842 00:56:16,520 --> 00:56:19,720 Speaker 1: telelimb to your body and it has relevance to you, 843 00:56:19,719 --> 00:56:22,680 Speaker 1: your body will learn how to use that, just like 844 00:56:22,840 --> 00:56:27,200 Speaker 1: Faith the dog mastered a unique body plan and learned 845 00:56:27,200 --> 00:56:29,800 Speaker 1: how to walk on her back legs because it mattered 846 00:56:29,840 --> 00:56:32,719 Speaker 1: to her. So the lesson I want to leave you 847 00:56:32,760 --> 00:56:35,360 Speaker 1: today with is when you need to learn something, find 848 00:56:35,360 --> 00:56:39,560 Speaker 1: some aspect of that that matters to you. My students 849 00:56:39,640 --> 00:56:42,680 Speaker 1: ask me this all the time about advice on getting 850 00:56:42,719 --> 00:56:44,879 Speaker 1: through their final exams, and I tell them it's all 851 00:56:44,920 --> 00:56:49,560 Speaker 1: about relevance. Figure out what is the aspect that matters 852 00:56:49,560 --> 00:56:51,719 Speaker 1: to you. You're facing this dumb exam that you might 853 00:56:51,760 --> 00:56:55,359 Speaker 1: not care about, but you do care about getting into 854 00:56:55,400 --> 00:56:57,920 Speaker 1: graduate school and this is one important wrong on the 855 00:56:58,000 --> 00:57:01,319 Speaker 1: ladder to get there. Or you want to impress that 856 00:57:01,480 --> 00:57:03,680 Speaker 1: girl or boy over there, and so you need to 857 00:57:03,680 --> 00:57:06,080 Speaker 1: study so you can have this stuff on the tip 858 00:57:06,120 --> 00:57:10,160 Speaker 1: of your tongue. Or you appreciate the sacrifice that your 859 00:57:10,160 --> 00:57:12,759 Speaker 1: parents made in getting you here and you want to 860 00:57:12,760 --> 00:57:14,840 Speaker 1: make them proud and that would be meaningful to you, 861 00:57:15,200 --> 00:57:18,960 Speaker 1: or whatever the personal details don't matter, but the key 862 00:57:19,120 --> 00:57:22,439 Speaker 1: is to remind yourself of the relevance so you can 863 00:57:22,560 --> 00:57:26,480 Speaker 1: plug into that, so you can get the right neurotransmitters present, 864 00:57:26,840 --> 00:57:29,439 Speaker 1: so they can make the impression, so that they can 865 00:57:29,840 --> 00:57:34,080 Speaker 1: make the information stick, so that you're not like Fred 866 00:57:34,120 --> 00:57:36,600 Speaker 1: Williams who swings at the tennis ball but whose brain 867 00:57:36,680 --> 00:57:41,000 Speaker 1: doesn't change, but instead you're taking in the information and 868 00:57:41,040 --> 00:57:44,680 Speaker 1: you're making these changes in your forests of neurons so 869 00:57:44,720 --> 00:57:46,480 Speaker 1: that you can recall it later. 870 00:57:47,080 --> 00:57:51,400 Speaker 2: That's what brain plasticity is all about. 871 00:57:54,520 --> 00:57:57,840 Speaker 1: Go to Eagleman dot com slash podcast for more information 872 00:57:57,960 --> 00:58:00,840 Speaker 1: and to find further reading on all of this. Send 873 00:58:00,880 --> 00:58:04,560 Speaker 1: me an email at podcast at eagleman dot com with 874 00:58:04,840 --> 00:58:08,439 Speaker 1: questions or discussion, and I'm making sporadic episodes in which 875 00:58:08,480 --> 00:58:13,720 Speaker 1: I address those until next time. I'm David Eagleman, and 876 00:58:13,760 --> 00:58:15,560 Speaker 1: this is Inner Cosmos.