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These are the user uploaded subtitles that are being translated: 1 00:00:03,569 --> 00:00:07,707 Freeman: Our minds store our entire lives... 2 00:00:09,642 --> 00:00:14,914 Our memories, our talents, our deepest desires. 3 00:00:16,347 --> 00:00:20,619 Tell no one, and our thoughts remain our own. 4 00:00:21,955 --> 00:00:26,125 But that might be about to change. 5 00:00:29,262 --> 00:00:33,131 Our brains are biological computers, 6 00:00:33,132 --> 00:00:35,701 vulnerable to data theft. 7 00:00:35,702 --> 00:00:38,870 Computer hackers can read our e-mail. 8 00:00:39,739 --> 00:00:43,809 Brain hackers may someday read our minds... 9 00:00:45,544 --> 00:00:48,982 And even rewrite our thoughts. 10 00:00:50,883 --> 00:00:53,253 Can our minds be hacked? 11 00:00:58,724 --> 00:01:03,529 Space, time, life itself. 12 00:01:05,598 --> 00:01:10,402 The secrets of the cosmos lie through the wormhole. 13 00:01:10,403 --> 00:01:13,405 Subtital By RA_One 15 00:01:21,000 --> 00:01:23,735 we live in a world of data. 16 00:01:23,736 --> 00:01:26,338 We all know how vital it is 17 00:01:26,339 --> 00:01:29,007 to protect our personal information, 18 00:01:29,008 --> 00:01:32,076 our passwords and credit-card numbers, 19 00:01:32,077 --> 00:01:35,347 but what if hackers learned to read or tamper with 20 00:01:35,348 --> 00:01:39,283 our most precious and private store of data... 21 00:01:39,284 --> 00:01:41,920 The contents of our minds? 22 00:01:41,921 --> 00:01:45,957 Can the brain be hacked by a computer? 23 00:01:45,958 --> 00:01:50,428 The data in our brain is not stored as simple ones and zeros. 24 00:01:50,429 --> 00:01:52,364 Hacking into our thoughts 25 00:01:52,365 --> 00:01:56,400 requires decoding the logic of our neurons. 26 00:01:56,401 --> 00:02:00,838 Science is getting close to achieving that goal. 27 00:02:00,839 --> 00:02:02,841 One day soon, 28 00:02:02,842 --> 00:02:07,513 our innermost thoughts may no longer be our own. 29 00:02:15,053 --> 00:02:19,257 I once tried to hide the truth from my mother. 30 00:02:19,258 --> 00:02:20,858 I lied, 31 00:02:20,859 --> 00:02:22,860 but when she looked into my eyes, 32 00:02:22,861 --> 00:02:26,799 I knew that she knew. 33 00:02:28,667 --> 00:02:30,669 How could she know? 34 00:02:31,737 --> 00:02:33,571 Man: How you doing? 35 00:02:33,572 --> 00:02:36,040 Please turn off your cellphones. 36 00:02:36,041 --> 00:02:39,710 Now put your hands together for the one and only Marc Salem. 37 00:02:39,711 --> 00:02:40,779 Enjoy the show. 38 00:02:40,780 --> 00:02:43,449 [ Cheers and applause ] 39 00:02:51,657 --> 00:02:53,491 It's only me. 40 00:02:53,492 --> 00:02:56,593 Good evening, everybody. I'm delighted to be here. 41 00:02:56,594 --> 00:03:00,698 What I'd like to do is choose somebody at random... 42 00:03:00,699 --> 00:03:02,527 Freeman: Marc Salem is one of new. 43 00:03:02,528 --> 00:03:04,569 York's most prominent psychologists, 44 00:03:04,570 --> 00:03:07,805 but he also has a remarkable talent, 45 00:03:07,806 --> 00:03:10,441 one that has catapulted him into show business. 46 00:03:10,442 --> 00:03:12,743 All right, here's what I want you to do. 47 00:03:12,744 --> 00:03:14,945 I want you to say "Stop" At any point. 48 00:03:14,946 --> 00:03:16,112 Say "Stop" At any point. 49 00:03:16,113 --> 00:03:17,247 Woman: Stop. Okay. 50 00:03:17,248 --> 00:03:18,884 Look at the first word on the first line. 51 00:03:18,984 --> 00:03:19,918 Have you got it? Yeah. 52 00:03:19,919 --> 00:03:22,320 Okay. Hold onto this. 53 00:03:23,622 --> 00:03:26,591 All right. Say nothing at all to me. 54 00:03:26,592 --> 00:03:30,029 Say nothing at all to me. Just think of the first letter. 55 00:03:31,430 --> 00:03:35,099 A, b, c, d, e, f, g, h, I, j, k, I, m, n, o, p, 56 00:03:35,100 --> 00:03:37,602 q, r, s, t, u, v, w, x, y, z. 57 00:03:37,603 --> 00:03:39,403 Okay. It's an "S." Is that correct? 58 00:03:39,404 --> 00:03:40,905 - Yes. - Okay, good. 59 00:03:40,906 --> 00:03:42,841 Let's see. The second letter, probably a vowel. 60 00:03:42,842 --> 00:03:46,077 A, e, I, o, u. A, e, I, o, u. 61 00:03:46,078 --> 00:03:48,046 - It's an "E, " Isn't it? - Yes. 62 00:03:48,047 --> 00:03:51,282 Freeman: Marc's mind-reading ability is not magic. 63 00:03:51,283 --> 00:03:54,818 He's reading tiny physical clues 64 00:03:54,819 --> 00:03:57,788 his subjects are unwittingly giving him. 65 00:03:57,789 --> 00:03:59,558 Se..."E." 66 00:03:59,759 --> 00:04:01,360 - the word is "Second"? - Yes. 67 00:04:01,361 --> 00:04:03,729 Give her a round of applause, please. 68 00:04:03,730 --> 00:04:05,864 What I'm looking for, first of all, 69 00:04:05,865 --> 00:04:08,200 is some kind of difference 70 00:04:08,201 --> 00:04:10,236 in the way that they're expressing themselves. 71 00:04:10,237 --> 00:04:12,438 Should I get rid of this one or this one? 72 00:04:12,439 --> 00:04:14,173 - That one. - Get rid of this one. 73 00:04:14,174 --> 00:04:16,877 I think every mental thought that we have 74 00:04:16,976 --> 00:04:21,080 has some physical corresponding emission. 75 00:04:21,181 --> 00:04:24,216 There's something that we can tell about that thought. 76 00:04:24,217 --> 00:04:26,485 We literally can see people thinking. 77 00:04:26,486 --> 00:04:30,689 My friends, let me just say once again, 78 00:04:30,690 --> 00:04:32,692 nothing that I did this evening is supernatural. 79 00:04:32,693 --> 00:04:34,660 Nothing that I do is occult. 80 00:04:34,661 --> 00:04:36,429 Thank you so very much. 81 00:04:36,430 --> 00:04:37,929 [ Applause ] 82 00:04:37,930 --> 00:04:42,735 Freeman: From his stage shows and from his academic research, 83 00:04:42,736 --> 00:04:44,170 Marc has learned 84 00:04:44,171 --> 00:04:47,740 that it's almost impossible to keep a secret. 85 00:04:47,741 --> 00:04:49,908 What our brains are thinking 86 00:04:49,909 --> 00:04:54,613 can't help but leak out into our physical bodies. 87 00:04:54,614 --> 00:04:57,749 Now, this light board is really somewhat like your brain 88 00:04:57,750 --> 00:05:00,052 in a simplistic form. 89 00:05:00,053 --> 00:05:05,123 We have impulses traveling out interdependently. 90 00:05:05,124 --> 00:05:07,426 That is, each relies on the other one. 91 00:05:07,427 --> 00:05:09,214 Freeman: Just as your brain 92 00:05:09,215 --> 00:05:11,730 controls every muscle in your body, 93 00:05:11,731 --> 00:05:13,265 our theater light board 94 00:05:13,266 --> 00:05:16,035 sends signals to every light in the house, 95 00:05:16,036 --> 00:05:18,404 and just as the light board 96 00:05:18,405 --> 00:05:20,806 operates groups of lights with a single command, 97 00:05:20,807 --> 00:05:23,075 so does the brain. 98 00:05:23,076 --> 00:05:25,377 For example, Clarissa, show what would happen 99 00:05:25,378 --> 00:05:27,146 if we switched switch number one. 100 00:05:27,147 --> 00:05:30,949 A single button triggers a complex set of actions. 101 00:05:30,950 --> 00:05:33,585 Lights turn on. Lights turn off. 102 00:05:33,586 --> 00:05:38,324 Others move or change color all at once. 103 00:05:38,325 --> 00:05:41,260 In the same way, when we think a thought, 104 00:05:41,261 --> 00:05:45,197 our brains trigger a whole set of movements in our bodies. 105 00:05:45,198 --> 00:05:46,399 Let's say suddenly, 106 00:05:46,400 --> 00:05:49,368 it occurred to the person that they look ridiculous. 107 00:05:49,369 --> 00:05:51,403 Hit number two, please. 108 00:05:51,404 --> 00:05:53,639 Suddenly, that thought would change, 109 00:05:53,640 --> 00:05:56,374 and the physical would also change. 110 00:05:56,375 --> 00:05:58,978 Perhaps a sly smile would come on someone's face. 111 00:05:58,979 --> 00:06:01,980 Psychologists like Marc 112 00:06:01,981 --> 00:06:06,819 call these involuntary muscle reactions information leakage. 113 00:06:06,820 --> 00:06:10,122 He believes there's no way to stop it, 114 00:06:10,123 --> 00:06:12,926 even if you have the perfect poker face. 115 00:06:13,327 --> 00:06:15,128 Hi, guys. I'm glad you're here. 116 00:06:15,129 --> 00:06:17,730 I know that you're, among other things, gamblers, 117 00:06:17,731 --> 00:06:20,168 and we're gonna try a little bit of an experiment 118 00:06:20,169 --> 00:06:21,468 with how you think 119 00:06:21,469 --> 00:06:24,204 and information you may be giving off... 120 00:06:24,205 --> 00:06:26,707 What sometimes you may call tells... 121 00:06:26,708 --> 00:06:29,809 What we're really looking at as nonverbal communication. 122 00:06:29,810 --> 00:06:32,814 Could everybody look at their card, please? 123 00:06:36,450 --> 00:06:38,618 Remember it and put it down. 124 00:06:38,619 --> 00:06:40,854 To play a game of poker, 125 00:06:40,855 --> 00:06:42,656 you need to prevent everyone at the table 126 00:06:42,657 --> 00:06:44,724 from guessing your cards, 127 00:06:44,725 --> 00:06:48,661 but Marc believes he can see through any player, 128 00:06:48,662 --> 00:06:52,299 no matter how blank their expression may be. 129 00:06:52,300 --> 00:06:54,101 Let's try you. 130 00:06:54,102 --> 00:06:56,202 Think red, black. 131 00:06:56,203 --> 00:06:58,572 Focus on it. Black, red, black, red. 132 00:06:58,573 --> 00:07:00,974 Black, black, black. Red, red. 133 00:07:00,975 --> 00:07:02,976 I think it's definitely black. Is that correct? 134 00:07:02,977 --> 00:07:04,178 - Yes. - Okay. 135 00:07:04,179 --> 00:07:06,746 Spades, clubs, spades, clubs. 136 00:07:06,747 --> 00:07:13,053 Okay, there's a rapid blinking, discomfort at the spades, 137 00:07:13,054 --> 00:07:15,155 so is it a spade? 138 00:07:15,156 --> 00:07:16,590 Okay. 139 00:07:16,591 --> 00:07:20,193 Ace, 2, 3, 4, 5, 6, 7, 8, 9, 10. 140 00:07:20,194 --> 00:07:22,197 Jack, queen, king. 141 00:07:23,698 --> 00:07:26,133 There was a very tight blink on the Jack, 142 00:07:26,134 --> 00:07:27,435 so I would think Jack. 143 00:07:32,206 --> 00:07:34,242 Salem: There are ways to know what people are thinking. 144 00:07:34,243 --> 00:07:36,843 You have to learn to pay attention 145 00:07:36,844 --> 00:07:39,278 to the subtle differences, the subtle nuances, 146 00:07:39,279 --> 00:07:40,514 and that's what I do. 147 00:07:40,515 --> 00:07:42,715 I try to look at what's normally done 148 00:07:42,716 --> 00:07:44,985 and then what those subtle nuances are 149 00:07:44,986 --> 00:07:46,553 and plus what are universal. 150 00:07:46,554 --> 00:07:48,455 Freeman: Natural mind readers like Marc 151 00:07:48,456 --> 00:07:53,360 can decipher thoughts from involuntary muscle movements, 152 00:07:53,361 --> 00:07:55,261 but cutting-edge technology 153 00:07:55,262 --> 00:07:59,165 could give brain hackers direct access to our thoughts, 154 00:07:59,166 --> 00:08:02,136 even if our muscles never move. 155 00:08:07,375 --> 00:08:11,711 Augie nieto is a fitness industry entrepreneur. 156 00:08:11,712 --> 00:08:15,248 In 2005, he was diagnosed with a.L.S. 157 00:08:15,249 --> 00:08:18,885 And soon became almost completely paralyzed. 158 00:08:18,886 --> 00:08:23,056 The only parts of his body he can move are his feet. 159 00:08:23,057 --> 00:08:26,259 He uses them to control a speech computer. 160 00:08:26,260 --> 00:08:30,596 Even these muscles will eventually degenerate, 161 00:08:30,597 --> 00:08:35,135 but he may not lose the ability to communicate. 162 00:08:35,136 --> 00:08:38,938 Neurotechnology pioneer Dr. Philip low 163 00:08:38,939 --> 00:08:42,909 is hoping to hack into augie's mind before it's too late. 164 00:08:42,910 --> 00:08:45,244 Philip and a team of engineers 165 00:08:45,245 --> 00:08:48,815 are building a state-of-the-art brain reader, 166 00:08:48,816 --> 00:08:50,651 a device they call the ibrain. 167 00:08:51,000 --> 00:08:54,670 I'm wearing the first portable brain monitor ever built, 168 00:08:54,671 --> 00:08:59,341 and what it is doing is it is recording my brain data. 169 00:08:59,342 --> 00:09:02,979 It is actually sending it over to our servers, 170 00:09:02,980 --> 00:09:05,748 and our algorithms can crunch it. 171 00:09:05,749 --> 00:09:09,585 Freeman: Every time we decide to move our muscles, 172 00:09:09,586 --> 00:09:13,289 billions of neurons fire miniature bolts of electricity 173 00:09:13,290 --> 00:09:15,224 inside our brains. 174 00:09:16,726 --> 00:09:19,161 Philip's electrically sensitive ibrain 175 00:09:19,162 --> 00:09:21,397 can detect these electrical pulses 176 00:09:21,398 --> 00:09:24,066 by measuring the small changes in voltage 177 00:09:24,067 --> 00:09:27,470 they produce on the surface of the scalp. 178 00:09:27,471 --> 00:09:31,140 By seeing the activation of particles of brain structures, 179 00:09:31,141 --> 00:09:35,245 we can tell, "Oh, this person is trying to move his hands." 180 00:09:37,514 --> 00:09:39,588 Freeman: Philip thought the ibrain 181 00:09:39,589 --> 00:09:41,484 might help patients like augie 182 00:09:41,485 --> 00:09:43,820 who, despite their paralysis, 183 00:09:43,821 --> 00:09:45,888 have healthy, functioning brains 184 00:09:45,889 --> 00:09:48,958 that can still send signals to their muscles. 185 00:09:48,959 --> 00:09:52,128 A.L.S. Patients do not have problems 186 00:09:52,129 --> 00:09:53,997 when it comes to their own brains. 187 00:09:53,998 --> 00:09:56,899 The areas that his brain is using 188 00:09:56,900 --> 00:10:02,004 in order to control these limbs, 189 00:10:02,005 --> 00:10:04,006 these areas are still working perfectly fine. 190 00:10:04,007 --> 00:10:05,576 They're just unemployed right now. 191 00:10:06,643 --> 00:10:09,811 Hi, augie. Nice to see you again. 192 00:10:09,812 --> 00:10:11,614 Freeman: If the ibrain 193 00:10:11,615 --> 00:10:15,217 can pick up augie's mental intention to move, 194 00:10:15,218 --> 00:10:20,222 Philip could create a new means for him to communicate. 195 00:10:20,223 --> 00:10:22,391 You will have a prompt. 196 00:10:22,392 --> 00:10:27,930 It will ask you to imagine to, you know, move your right hand 197 00:10:27,931 --> 00:10:29,932 for four seconds at a time, 198 00:10:29,933 --> 00:10:32,233 and, of course, we're going to be monitoring your brain waves 199 00:10:32,234 --> 00:10:33,670 very, very closely during that time 200 00:10:33,671 --> 00:10:36,706 and having all of our algorithms crunch the data 201 00:10:36,707 --> 00:10:38,941 in the background, as well. 202 00:10:38,942 --> 00:10:41,877 The test is successful. 203 00:10:41,878 --> 00:10:44,147 Philip's ibrain recognizes 204 00:10:44,148 --> 00:10:49,418 whenever augie is thinking about moving his right or left hand. 205 00:10:49,419 --> 00:10:52,355 Low: Augie had a very successful first test. 206 00:10:52,356 --> 00:10:54,390 We will use these brain patterns 207 00:10:54,391 --> 00:10:58,060 in order to control a virtual hand on the screen, 208 00:10:58,061 --> 00:11:00,595 which will enable him to just pick these words 209 00:11:00,596 --> 00:11:03,432 and pick these letters and enable him to communicate, 210 00:11:03,433 --> 00:11:06,635 so this gives us a lot of hope and encouragement 211 00:11:06,636 --> 00:11:09,972 that, in fact, we have a system that will work for everybody 212 00:11:09,973 --> 00:11:13,575 and that will enable individuals to use their brain patterns 213 00:11:13,576 --> 00:11:15,077 in order to communicate. 214 00:11:15,078 --> 00:11:18,080 Man: The biggest fear for someone with a.L.S. 215 00:11:18,081 --> 00:11:20,148 Is to be not able to communicate. 216 00:11:20,149 --> 00:11:21,718 That is called being locked in. 217 00:11:21,719 --> 00:11:25,923 With the ibrain, I will never, never be locked in! 218 00:11:28,258 --> 00:11:30,128 Freeman: Soon, augie may not even 219 00:11:30,129 --> 00:11:32,161 have to think about moving his hand 220 00:11:32,162 --> 00:11:34,129 in order to communicate 221 00:11:34,130 --> 00:11:37,633 because a laboratory in California 222 00:11:37,634 --> 00:11:39,902 has already begun to translate thoughts 223 00:11:39,903 --> 00:11:43,340 into pictures and words. 224 00:11:46,000 --> 00:11:49,269 We all have thoughts we'd rather keep to ourselves. 225 00:11:49,270 --> 00:11:53,040 When computer scientists want to keep something secret, 226 00:11:53,041 --> 00:11:54,942 they encrypt it, 227 00:11:54,943 --> 00:11:59,078 but it's just a matter of time before any code is cracked. 228 00:11:59,079 --> 00:12:01,314 The electrical activity buzzing 229 00:12:01,315 --> 00:12:03,916 between the neurons in our brains 230 00:12:03,917 --> 00:12:06,986 could be the next code we decipher. 231 00:12:06,987 --> 00:12:09,822 In fact, some neuroscientists 232 00:12:09,823 --> 00:12:13,426 are already translating the language of the brain 233 00:12:13,427 --> 00:12:16,196 into plain English. 234 00:12:16,197 --> 00:12:19,866 Neuroscientist Jack gallant is on a mission 235 00:12:19,867 --> 00:12:23,336 to translate the flurry of activity inside our heads 236 00:12:23,337 --> 00:12:25,872 into plain English. 237 00:12:25,873 --> 00:12:29,175 You might say he's writing the book on it. 238 00:12:29,176 --> 00:12:32,879 Gallant: You can think of each part of the brain 239 00:12:32,880 --> 00:12:34,380 as translating between the world 240 00:12:34,381 --> 00:12:37,116 and whatever the brain activity is in that part of the brain, 241 00:12:37,117 --> 00:12:39,786 so there's some sort of language you can think of 242 00:12:39,787 --> 00:12:42,289 that's gonna mediate between the world and the brain, 243 00:12:42,290 --> 00:12:44,257 and if you had a list of all of the things 244 00:12:44,258 --> 00:12:46,124 that related the world to the brain, 245 00:12:46,125 --> 00:12:48,095 you would essentially have a dictionary. 246 00:12:48,096 --> 00:12:49,696 Freeman: The first brain 247 00:12:49,697 --> 00:12:52,031 dictionary Jack set out to build 248 00:12:52,032 --> 00:12:56,102 was for the language of sight. 249 00:12:56,103 --> 00:12:58,572 There are about 50 or 70 brain areas 250 00:12:58,573 --> 00:13:00,307 that are devoted to vision, 251 00:13:00,308 --> 00:13:01,607 so there's gonna be, essentially, 252 00:13:01,608 --> 00:13:03,142 50 or 70 different dictionaries 253 00:13:03,143 --> 00:13:04,778 that we're gonna have to build... 254 00:13:04,779 --> 00:13:06,846 One dictionary for each region of the brain. 255 00:13:06,847 --> 00:13:08,614 Now, that's gonna be a really big dictionary. 256 00:13:08,615 --> 00:13:10,115 It's gonna be much thicker than this 257 00:13:10,116 --> 00:13:12,084 because the number of things you can see in the world 258 00:13:12,085 --> 00:13:15,356 is really, really a large number. 259 00:13:17,558 --> 00:13:20,260 Freeman: To build a brain dictionary, 260 00:13:20,261 --> 00:13:25,432 Jack and his colleagues shinji nishimoto and Alex huth 261 00:13:25,433 --> 00:13:30,771 use an fmri scanner to measure exactly how the brain responds 262 00:13:30,772 --> 00:13:33,307 to a long series of video clips. 263 00:13:35,209 --> 00:13:36,975 So, this is a viewer that allows us 264 00:13:36,976 --> 00:13:39,380 to visualize the blood flow while the movie plays. 265 00:13:39,381 --> 00:13:41,848 Blue means relatively less blood flow, 266 00:13:41,849 --> 00:13:44,483 and red means relatively more blood flow, 267 00:13:44,484 --> 00:13:45,751 and you can see 268 00:13:45,752 --> 00:13:47,821 that the blood flow's changing quite dramatically 269 00:13:47,822 --> 00:13:50,390 as the scenes in this movie play, 270 00:13:50,391 --> 00:13:53,960 and the problem that we have in modeling the brain 271 00:13:53,961 --> 00:13:56,062 is to try to understand what the relationship is 272 00:13:56,063 --> 00:14:01,401 between each individual point in this brain and these movies. 273 00:14:01,402 --> 00:14:05,906 Freeman: But as they compiled thousands of scans of brains 274 00:14:05,907 --> 00:14:08,141 reacting to thousands of frames of video, 275 00:14:08,142 --> 00:14:11,611 Jack and his team found that certain objects 276 00:14:11,612 --> 00:14:15,014 trigger predictable patterns of blood flow, 277 00:14:15,015 --> 00:14:16,750 and they began to build 278 00:14:16,751 --> 00:14:19,586 a dictionary of objects in the world, 279 00:14:19,587 --> 00:14:23,256 defined as particular patterns of blood flow in the brain. 280 00:14:23,257 --> 00:14:26,125 Gallant: And then once we have this world-brain dictionary, 281 00:14:26,126 --> 00:14:27,527 we can actually take it, 282 00:14:27,528 --> 00:14:29,696 and we can sort of run it backwards, 283 00:14:29,697 --> 00:14:31,599 and we can create a brain-world dictionary. 284 00:14:33,567 --> 00:14:36,169 Freeman: To test that dictionary, 285 00:14:36,170 --> 00:14:39,572 they send their test subjects back into the fmri 286 00:14:39,573 --> 00:14:41,107 to watch more movies, 287 00:14:41,108 --> 00:14:45,211 except this time, they don't see what the subject sees. 288 00:14:45,212 --> 00:14:49,281 Jack and his team have to guess using only the raw data 289 00:14:49,282 --> 00:14:54,287 from the brain scans and an advanced computer algorithm. 290 00:14:54,288 --> 00:14:56,189 So, there are probably, say, 291 00:14:56,190 --> 00:14:58,524 10,000 points on the brain, 5,000, 292 00:14:58,525 --> 00:15:00,861 that are being used in this model, 293 00:15:00,862 --> 00:15:05,231 and each point in the brain has a predicted brain activity 294 00:15:05,232 --> 00:15:07,701 that it generates when you stick an image through it, 295 00:15:07,702 --> 00:15:09,369 and then we aggregate information 296 00:15:09,370 --> 00:15:10,770 across all those 10,000 points 297 00:15:10,771 --> 00:15:12,640 to come up with the best prediction. 298 00:15:12,641 --> 00:15:18,211 Freeman: This is the image that only the subject could see. 299 00:15:18,212 --> 00:15:21,548 These are the top choices the computer selects 300 00:15:21,549 --> 00:15:23,816 from the brain-world dictionary, 301 00:15:23,817 --> 00:15:28,621 and this is the composite average. 302 00:15:28,622 --> 00:15:32,425 No matter what the subject sees in the world, 303 00:15:32,426 --> 00:15:37,431 the brain-world dictionary can produce a rough copy. 304 00:15:39,600 --> 00:15:41,434 But this algorithm does more 305 00:15:41,435 --> 00:15:44,637 than just guess what images people are watching. 306 00:15:44,638 --> 00:15:50,242 It can also guess what they are thinking about those images. 307 00:15:50,243 --> 00:15:53,279 Here on the left is the movie that the subjects saw, 308 00:15:53,280 --> 00:15:56,483 and on the right, you can see 2,000 nouns and verbs, 309 00:15:56,484 --> 00:15:58,785 and they change their size, 310 00:15:58,786 --> 00:16:02,021 and the size of the word indicates the probability 311 00:16:02,022 --> 00:16:05,391 that that concept appeared in the video at that time. 312 00:16:05,392 --> 00:16:06,695 You can see here, it gets "Talk, " 313 00:16:06,696 --> 00:16:08,295 "Face, " "Woman, " "Man." 314 00:16:08,296 --> 00:16:10,363 here, "Talking, " "Man." 315 00:16:10,364 --> 00:16:14,100 you'll see, here's "Hand, " "Room, " "Face." 316 00:16:14,101 --> 00:16:16,469 so, this is a complicated scene. 317 00:16:16,470 --> 00:16:19,639 Here we go. We switch to an ocean scene. 318 00:16:19,640 --> 00:16:22,107 "Clouds, " "Sky, " "Vegetation" "Waikiki, " 319 00:16:22,108 --> 00:16:23,642 "Body of water, " "Building, " 320 00:16:23,643 --> 00:16:25,612 "Sky, " "People walking, " "Tree." 321 00:16:25,613 --> 00:16:30,883 these are all really very accurate semantic decodings. 322 00:16:30,884 --> 00:16:33,086 Freeman: Jack's team has built 323 00:16:33,087 --> 00:16:36,789 a dictionary of 2,000 emotionally neutral concepts 324 00:16:36,790 --> 00:16:38,324 that people might think 325 00:16:38,325 --> 00:16:40,994 when they watch their series of videos. 326 00:16:40,995 --> 00:16:44,697 Calibrating their computers to decode more personal meaning 327 00:16:44,698 --> 00:16:46,866 is only a matter of time 328 00:16:46,867 --> 00:16:51,537 and increasing the level of detail in the brain scans. 329 00:16:51,538 --> 00:16:53,239 We're constantly surprised 330 00:16:53,240 --> 00:16:55,909 by how much information we can recover, 331 00:16:55,910 --> 00:16:57,110 especially given 332 00:16:57,111 --> 00:16:58,677 that the measurements we're taking of the brain 333 00:16:58,678 --> 00:17:00,847 are still, at this point, really, really primitive. 334 00:17:00,848 --> 00:17:03,449 That's one thing that I think is really exciting about this field 335 00:17:03,450 --> 00:17:04,918 and really interesting, 336 00:17:04,919 --> 00:17:07,455 and I also think it raises a caution flag 337 00:17:07,554 --> 00:17:11,124 that I think we're gonna have to deal with these ethical issues 338 00:17:11,125 --> 00:17:13,692 involving brain decoding sooner rather than later, 339 00:17:13,693 --> 00:17:14,862 because we don't know 340 00:17:14,863 --> 00:17:17,063 how fast this technology's gonna progress, 341 00:17:17,064 --> 00:17:19,398 and that opens up a big ethical can of worms. 342 00:17:19,399 --> 00:17:21,401 You know, when is that gonna be used? 343 00:17:21,402 --> 00:17:22,837 And what can it be used for? 344 00:17:22,838 --> 00:17:25,405 And I really think this needs to get addressed right away. 345 00:17:25,406 --> 00:17:27,538 Freeman: Brain hackers may soon be 346 00:17:27,539 --> 00:17:29,608 able to read your every thought. 347 00:17:29,609 --> 00:17:30,910 What then? 348 00:17:30,911 --> 00:17:35,715 If your thoughts can be decoded, could they be altered? 349 00:17:35,716 --> 00:17:39,118 This neuroscientist and entrepreneur 350 00:17:39,119 --> 00:17:41,387 is pushing the boundaries of brain manipulation 351 00:17:41,388 --> 00:17:43,089 with a device 352 00:17:43,090 --> 00:17:48,129 that could turn amateurs into experts in a single day. 353 00:17:51,969 --> 00:17:55,370 We'd all love to be truly great at something... 354 00:17:55,371 --> 00:17:59,408 Maybe a physicist like Einstein 355 00:17:59,409 --> 00:18:02,778 or an artist like Picasso 356 00:18:02,779 --> 00:18:06,982 or a great leader like Nelson mandela. 357 00:18:06,983 --> 00:18:08,851 Most of us have to settle 358 00:18:08,852 --> 00:18:11,821 for simply good instead of incredible, 359 00:18:11,822 --> 00:18:17,894 but what if we could change that by hacking our mental software 360 00:18:17,895 --> 00:18:20,529 and giving ourselves capabilities 361 00:18:20,530 --> 00:18:23,200 we weren't born with? 362 00:18:25,435 --> 00:18:29,472 Chris berka is a neuroscientist, engineer, inventor, 363 00:18:29,473 --> 00:18:33,876 and c.E.O. Of a neurotech startup company. 364 00:18:33,877 --> 00:18:36,845 It's a workload that would crush most of us, 365 00:18:36,846 --> 00:18:38,881 but she handles it by getting into 366 00:18:38,882 --> 00:18:42,352 a high-performance, high-output brain state. 367 00:18:42,353 --> 00:18:46,421 It's what athletes call "The zone." 368 00:18:46,422 --> 00:18:48,090 berka: Being in the zone, 369 00:18:48,091 --> 00:18:50,760 it's essentially just focused attention 370 00:18:50,761 --> 00:18:54,063 and the ability to not be distracted. 371 00:18:54,064 --> 00:19:01,270 It's what allows you to really develop perfection in any skill. 372 00:19:01,271 --> 00:19:03,490 Freeman: Getting into the zone is 373 00:19:03,491 --> 00:19:05,708 a full-time obsession for Chris. 374 00:19:05,709 --> 00:19:08,144 Her company is developing a device 375 00:19:08,145 --> 00:19:10,379 that she claims can train your brain 376 00:19:10,380 --> 00:19:13,350 to work like the brain of a highly-skilled expert. 377 00:19:27,998 --> 00:19:30,033 Chris oosterlinck 378 00:19:30,034 --> 00:19:34,170 is a California state archery champion. 379 00:19:34,171 --> 00:19:36,238 Berka: He has a small band around his head 380 00:19:36,239 --> 00:19:37,374 that has four sensors 381 00:19:37,375 --> 00:19:39,442 for sensing the brain's electrical activity. 382 00:19:39,443 --> 00:19:42,111 We're gonna be looking for the particular state 383 00:19:42,112 --> 00:19:43,278 leading up to the shot 384 00:19:43,279 --> 00:19:45,081 that we know is the peak performance state. 385 00:19:45,082 --> 00:19:47,051 So, Chris, do you want to get ready and go? 386 00:19:55,525 --> 00:19:59,762 Freeman: Inside Chris' brain, billions of neurons are firing, 387 00:19:59,763 --> 00:20:01,864 creating waves of electricity. 388 00:20:01,865 --> 00:20:06,702 Different states of mind have different frequencies of waves. 389 00:20:06,703 --> 00:20:11,207 When people are in the zone, two frequencies dominate... 390 00:20:11,208 --> 00:20:12,508 Alpha waves, 391 00:20:12,509 --> 00:20:15,211 which indicate a state of meditative concentration, 392 00:20:15,212 --> 00:20:17,547 like those of a zen master, 393 00:20:17,548 --> 00:20:22,852 and lower-frequency theta waves, which show extreme relaxation. 394 00:20:22,853 --> 00:20:26,256 Berka: The red line indicates the e.E.G. Theta activity, 395 00:20:26,257 --> 00:20:29,225 and the green line indicates the Alpha activity, 396 00:20:29,226 --> 00:20:31,995 and we see both of those Alpha and theta increase 397 00:20:31,996 --> 00:20:34,131 just prior to taking the perfect shot. 398 00:20:45,944 --> 00:20:49,046 Freeman: Chris brings in a group of amateurs. 399 00:20:49,047 --> 00:20:50,981 She wants to see what will happen 400 00:20:50,982 --> 00:20:55,452 if she coaxes the amateurs to take their shots 401 00:20:55,453 --> 00:20:58,656 while in the same brain state as a professional archer. 402 00:21:02,060 --> 00:21:03,961 Berka: So, what we're doing is 403 00:21:03,962 --> 00:21:05,963 monitoring the brain's electrical activity. 404 00:21:05,964 --> 00:21:08,799 We do that by putting sensors on the scalp, 405 00:21:08,800 --> 00:21:10,167 and as you move through 406 00:21:10,168 --> 00:21:12,803 different cognitive states and mental states, 407 00:21:12,804 --> 00:21:14,806 the electronic frequencies of your brain will change, 408 00:21:14,807 --> 00:21:18,142 and we can record those in real time and analyze them. 409 00:21:18,143 --> 00:21:22,079 Freeman: Each amateur focuses and relaxes to reach the zone. 410 00:21:22,080 --> 00:21:25,216 Chris' monitor records their brain waves, 411 00:21:25,217 --> 00:21:28,353 and a small haptic buzzer on their collar 412 00:21:28,354 --> 00:21:30,288 lets them know when they've achieved 413 00:21:30,289 --> 00:21:34,092 the same brain state as the professional. 414 00:21:34,093 --> 00:21:37,127 We're seeing the e.E.G. Alpha increase and theta increase. 415 00:21:37,128 --> 00:21:38,530 The haptic buzzer stopped, 416 00:21:38,531 --> 00:21:40,932 and now he's ready to take the perfect shot. 417 00:21:40,933 --> 00:21:42,468 Go ahead, Shane. 418 00:21:50,141 --> 00:21:53,510 That was perfect. [ Chuckles ] That was perfect. 419 00:21:53,511 --> 00:21:55,479 That's exactly the goal. 420 00:21:55,480 --> 00:21:58,182 Freeman: By the end of only one day of practice, 421 00:21:58,183 --> 00:22:01,585 Chris' technology hacked the minds of a group of amateurs 422 00:22:01,586 --> 00:22:07,958 to shoot at or close to a professional level of expertise. 423 00:22:07,959 --> 00:22:10,060 Berka: And what we're able to demonstrate 424 00:22:10,061 --> 00:22:13,163 is a 230% increase in the speed and accuracy 425 00:22:13,164 --> 00:22:16,234 of marksmanship training. 426 00:22:17,669 --> 00:22:20,537 Freeman: Chris sees no end of potential customers 427 00:22:20,538 --> 00:22:23,741 for her brain-hacking device... 428 00:22:23,742 --> 00:22:28,712 A corporate board that needs to make smart group decisions, 429 00:22:28,713 --> 00:22:32,382 a president who needs peak performance, 430 00:22:32,383 --> 00:22:35,953 or a special-forces operative whose split-second choices 431 00:22:35,954 --> 00:22:40,090 make the difference between life and death. 432 00:22:40,091 --> 00:22:42,994 What we're trying to do is to give you the ability 433 00:22:42,995 --> 00:22:46,263 to control your mind and your mental state, 434 00:22:46,264 --> 00:22:48,132 your ability to deal with 435 00:22:48,133 --> 00:22:51,102 even the most challenging environments, 436 00:22:51,103 --> 00:22:54,838 and just by training you to control your brain, 437 00:22:54,839 --> 00:22:58,375 you get this kind of metacognitive awareness 438 00:22:58,376 --> 00:23:01,745 that allows you to be much more resilient 439 00:23:01,746 --> 00:23:04,916 and adaptable to stressful situations. 440 00:23:05,917 --> 00:23:11,687 If we can hack into our own brains to amplify our talents, 441 00:23:11,688 --> 00:23:16,959 what's stopping us from hacking into the brains of other people? 442 00:23:16,960 --> 00:23:21,098 Could one mind reprogram the reality of another? 443 00:23:24,535 --> 00:23:26,803 Let's do an experiment. 444 00:23:26,804 --> 00:23:29,005 Close your eyes. 445 00:23:29,006 --> 00:23:31,307 Keep them closed. 446 00:23:31,308 --> 00:23:34,411 Now imagine you're alone in the desert 447 00:23:34,412 --> 00:23:36,450 and your throat and mouth are swollen with thirst. 448 00:23:38,000 --> 00:23:41,303 Now think about drinking a cool glass of water. 449 00:23:43,471 --> 00:23:45,472 Open your eyes. 450 00:23:45,473 --> 00:23:48,142 Do you feel refreshed? 451 00:23:48,143 --> 00:23:49,543 If you do, 452 00:23:49,544 --> 00:23:55,417 I just hacked into your mind and altered your perception. 453 00:23:58,754 --> 00:24:02,623 Stanford's David spiegel is not your typical psychiatrist. 454 00:24:02,624 --> 00:24:05,793 He helps his patients overcome their struggles 455 00:24:05,794 --> 00:24:07,995 through a technique that is controversial 456 00:24:07,996 --> 00:24:10,365 for a university doctor... 457 00:24:10,366 --> 00:24:13,333 Hypnosis. 458 00:24:13,334 --> 00:24:16,503 Hypnosis is a form of highly focused attention 459 00:24:16,504 --> 00:24:19,206 coupled with an ability to dissociate, 460 00:24:19,207 --> 00:24:21,209 or put outside of conscious awareness, 461 00:24:21,210 --> 00:24:23,645 things that would ordinarily be in consciousness 462 00:24:23,646 --> 00:24:27,581 and a heightened response to social cues or suggestibility. 463 00:24:27,582 --> 00:24:30,518 And hypnosis is highly focused attention. 464 00:24:30,519 --> 00:24:33,489 It's been called believed-in imagination. 465 00:24:37,692 --> 00:24:39,894 Freeman: David wanted to know 466 00:24:39,895 --> 00:24:43,564 how people perceived the world when hypnotized, 467 00:24:43,565 --> 00:24:48,135 so he has designed an experiment to look at the brains of people 468 00:24:48,136 --> 00:24:52,508 who have the ability to hypnotize themselves. 469 00:24:53,608 --> 00:24:55,576 Okay, Katie, you doing all right? 470 00:24:55,577 --> 00:24:56,778 Katie: Yep. 471 00:24:56,877 --> 00:24:58,111 - Good. - All right, now, 472 00:24:58,812 --> 00:25:01,582 we're gonna go into a state of self-hypnosis now. 473 00:25:01,583 --> 00:25:02,750 Uh-huh. 474 00:25:02,751 --> 00:25:05,519 So now I want your eyes to be relaxed and closed, 475 00:25:05,520 --> 00:25:08,956 and imagine your body floating somewhere safe and comfortable, 476 00:25:08,957 --> 00:25:12,759 like a bath, a lake, a hot tub, or just floating in space. 477 00:25:12,760 --> 00:25:14,962 Each breath deeper and easier. 478 00:25:14,963 --> 00:25:17,698 Body floating safe and comfortable. 479 00:25:17,699 --> 00:25:20,901 Once she is under hypnosis, 480 00:25:20,902 --> 00:25:24,204 David shows Katie a grid of colors. 481 00:25:24,205 --> 00:25:27,242 What colors do you see now? Just name a few. 482 00:25:33,915 --> 00:25:35,315 Good. 483 00:25:35,316 --> 00:25:38,819 Katie perceives the color grid, 484 00:25:38,820 --> 00:25:42,890 and her fusiform gyrus lights up. 485 00:25:42,891 --> 00:25:47,962 This part of the brain becomes active whenever we see color. 486 00:25:47,963 --> 00:25:50,865 But because Katie's under hypnosis, 487 00:25:50,866 --> 00:25:53,902 David can now tamper with her senses. 488 00:25:55,270 --> 00:25:57,838 And now I want you to drain the color 489 00:25:57,839 --> 00:26:01,575 from the image in front of you 490 00:26:01,576 --> 00:26:06,380 so that what you start to see is just gray, white, and black. 491 00:26:06,381 --> 00:26:08,517 Just drain away the color. 492 00:26:10,852 --> 00:26:14,622 Now again, remaining in this state of concentration, Katie, 493 00:26:14,623 --> 00:26:19,228 please tell me what the image looks like to you now. 494 00:26:30,538 --> 00:26:32,306 - Good. - Yeah. 495 00:26:32,307 --> 00:26:36,677 Physically, the color image has not changed, 496 00:26:36,678 --> 00:26:43,116 but David now takes another scan of Katie's fusiform gyrus. 497 00:26:43,117 --> 00:26:44,419 Spiegel: So, we're looking now 498 00:26:44,420 --> 00:26:45,720 at the regions of the brain 499 00:26:45,721 --> 00:26:47,487 that actually light up, 500 00:26:47,488 --> 00:26:50,258 because there's more blood flow when they're looking at color 501 00:26:50,259 --> 00:26:52,392 than when they're looking at black and white. 502 00:26:52,393 --> 00:26:54,228 Here is what the blood flow was 503 00:26:54,229 --> 00:26:56,697 when they were really looking at color, 504 00:26:56,698 --> 00:26:59,101 and here's the blood flow when they were looking at color 505 00:26:59,102 --> 00:27:02,002 but drained it of color and saw it as black and white. 506 00:27:02,003 --> 00:27:06,006 Freeman: Even though she's still looking at a color image, 507 00:27:06,007 --> 00:27:10,477 the blood flow to Katie's fusiform gyrus is decreasing. 508 00:27:10,478 --> 00:27:12,880 It is proof that her brain 509 00:27:12,881 --> 00:27:16,316 is turning off her ability to see color 510 00:27:16,317 --> 00:27:18,685 at David's suggestion. 511 00:27:18,686 --> 00:27:22,159 The image she perceives is becoming black and white. 512 00:27:24,860 --> 00:27:27,830 David believes that hypnosis opened up Katie's brain 513 00:27:27,831 --> 00:27:28,931 for reprogramming. 514 00:27:29,000 --> 00:27:31,502 His thoughts hacked into her mind 515 00:27:31,503 --> 00:27:36,173 and became her real living experience. 516 00:27:36,174 --> 00:27:40,211 We tend to think that the brain processes raw information 517 00:27:40,212 --> 00:27:42,879 and we make sense of it afterwards, 518 00:27:42,880 --> 00:27:44,247 but it turns out, 519 00:27:44,248 --> 00:27:46,951 especially in studies of hypnosis, 520 00:27:46,952 --> 00:27:48,417 that we can reset the brain, 521 00:27:48,418 --> 00:27:49,821 that we can change the way 522 00:27:49,822 --> 00:27:52,055 the brain actually perceives information, 523 00:27:52,056 --> 00:27:54,992 so it's not that it reacts differently to the same input. 524 00:27:54,993 --> 00:27:57,494 It changes what the input is. 525 00:27:57,495 --> 00:28:01,898 Freeman: David's work suggests that while under hypnosis, 526 00:28:01,899 --> 00:28:06,404 the way our brains perceive reality is altered. 527 00:28:07,705 --> 00:28:11,542 I had a student who was doing research with me on hypnosis 528 00:28:11,543 --> 00:28:15,479 who is also a really talented athlete for the football team. 529 00:28:15,480 --> 00:28:18,749 He was terrific, and he was very hypnotizable, 530 00:28:18,750 --> 00:28:20,083 and I would say to him, 531 00:28:20,084 --> 00:28:22,554 "So, what's going on when you're playing like this?" 532 00:28:22,555 --> 00:28:25,021 he said, "Doc, when I'm having a good day, 533 00:28:25,022 --> 00:28:26,690 I'm aware of two things. 534 00:28:26,691 --> 00:28:29,760 I'm aware of the football and the defender." 535 00:28:29,761 --> 00:28:31,328 [ crowd cheering ] 536 00:28:31,329 --> 00:28:33,964 And he said, "And there's 20 other big guys on the field. 537 00:28:33,965 --> 00:28:35,297 I don't know they're there. 538 00:28:35,298 --> 00:28:37,702 There's 60,000 people yelling at me from the stands. 539 00:28:37,703 --> 00:28:39,336 I don't hear them." 540 00:28:39,337 --> 00:28:42,372 clearly, our minds are programmable. 541 00:28:42,373 --> 00:28:45,308 We have hardware that allows us to take in input, process it, 542 00:28:45,309 --> 00:28:46,545 and do something with it, 543 00:28:46,546 --> 00:28:48,778 and that input can come from ourself 544 00:28:48,779 --> 00:28:50,748 or from people around us. 545 00:28:50,749 --> 00:28:56,620 Freeman: Hypnotism opens our minds to brain hackers, 546 00:28:56,621 --> 00:28:58,822 but we have to make a conscious choice 547 00:28:58,823 --> 00:29:00,258 to enter a hypnotic state, 548 00:29:00,259 --> 00:29:03,460 like a computer that can accept or reject 549 00:29:03,461 --> 00:29:05,296 another user logging on. 550 00:29:06,029 --> 00:29:11,366 There may be a hole in our neurological security, however. 551 00:29:11,367 --> 00:29:14,469 A team of researchers in Tel Aviv 552 00:29:14,470 --> 00:29:16,738 claims to have found an exploit 553 00:29:16,739 --> 00:29:20,309 that could open our unconscious mind to hackers. 554 00:29:22,000 --> 00:29:25,436 Freeman: Think back to your childhood. 555 00:29:25,437 --> 00:29:27,204 What do you recall? 556 00:29:27,205 --> 00:29:30,008 Your mother's perfume? 557 00:29:30,009 --> 00:29:32,210 Fresh-cut grass? 558 00:29:32,211 --> 00:29:35,179 Oatmeal cookies baking in the oven? 559 00:29:35,180 --> 00:29:38,115 A familiar scent can flood the mind 560 00:29:38,116 --> 00:29:41,686 with images, memories, and emotions 561 00:29:41,687 --> 00:29:44,789 whether we like it or not. 562 00:29:44,790 --> 00:29:48,393 Computer hackers write programs called cracks 563 00:29:48,394 --> 00:29:51,328 to break into secure systems. 564 00:29:51,329 --> 00:29:56,802 Could your sense of smell be a crack for a brain hacker? 565 00:30:04,810 --> 00:30:08,045 Ilana hairston is a research psychologist 566 00:30:08,046 --> 00:30:09,647 in Tel Aviv, Israel. 567 00:30:09,648 --> 00:30:13,651 Ilana is fascinated by what happens in our brains 568 00:30:13,652 --> 00:30:15,453 when we sleep. 569 00:30:15,454 --> 00:30:20,525 It began with an experiment she did in her student days. 570 00:30:20,526 --> 00:30:22,561 Hairston: At the time, I was working with animals, 571 00:30:22,562 --> 00:30:25,129 and I could see that I would train animals on a maze 572 00:30:25,130 --> 00:30:27,899 and they would not learn. 573 00:30:27,900 --> 00:30:30,002 "Clearly, " I thought, "These animals are very stupid, " 574 00:30:30,003 --> 00:30:32,002 and then I'd go back, put them in the cage, 575 00:30:32,003 --> 00:30:34,005 come back the next day, and boom, 576 00:30:34,006 --> 00:30:37,007 they performed like they'd been practicing the whole night, 577 00:30:37,008 --> 00:30:38,776 and it just blew my mind. 578 00:30:38,777 --> 00:30:42,580 It made me realize we spend a third of our life asleep, 579 00:30:42,581 --> 00:30:45,716 and there's so much going on while we sleep. 580 00:30:45,717 --> 00:30:47,553 Freeman: Ilana thinks that our 581 00:30:47,554 --> 00:30:49,387 minds must be able to learn 582 00:30:49,388 --> 00:30:51,055 when we lose consciousness. 583 00:30:51,056 --> 00:30:56,795 To prove it, she's plotting to break into the sleeping mind. 584 00:30:56,796 --> 00:30:59,998 It's a job that requires her to first get past 585 00:30:59,999 --> 00:31:03,768 the brain's night watchman, the thalamus. 586 00:31:03,769 --> 00:31:06,171 Hairston: There's a part of the brain called the thalamus. 587 00:31:06,172 --> 00:31:07,705 What it typically does, 588 00:31:07,706 --> 00:31:10,341 it's gonna clamp down on sensory information 589 00:31:10,342 --> 00:31:12,009 and stop you from waking up, 590 00:31:12,010 --> 00:31:15,046 or if it says, "Okay, this is important information. 591 00:31:15,047 --> 00:31:17,949 You need to wake up, " It'll cause you to wake up. 592 00:31:17,950 --> 00:31:19,940 Freeman: But Ilana believes there 593 00:31:19,941 --> 00:31:21,753 is a back door into the brain 594 00:31:21,754 --> 00:31:23,754 when we sleep... 595 00:31:23,755 --> 00:31:26,157 Our sense of smell. 596 00:31:26,158 --> 00:31:29,195 Smell goes first to the cortex... 597 00:31:30,929 --> 00:31:34,132 And so it kind of bypasses this relay station. 598 00:31:34,133 --> 00:31:37,035 Basically, you can enter the sleeping brain 599 00:31:37,036 --> 00:31:39,270 without going through this relay station. 600 00:31:39,271 --> 00:31:41,439 Freeman: When we fall asleep, 601 00:31:41,440 --> 00:31:44,576 the thalamus acts like a watchful nanny. 602 00:31:44,577 --> 00:31:48,446 Our senses try to deliver information to the brain 603 00:31:48,447 --> 00:31:50,081 but are turned away. 604 00:31:50,082 --> 00:31:53,518 Input from our sense of smell, however, 605 00:31:53,519 --> 00:31:55,987 has direct access, 606 00:31:55,988 --> 00:31:57,488 and once inside, 607 00:31:57,489 --> 00:32:00,792 sensory signals that are normally tuned out 608 00:32:00,793 --> 00:32:02,660 during our sleep 609 00:32:02,661 --> 00:32:04,563 can be snuck in. 610 00:32:06,398 --> 00:32:08,732 Ilana teamed up with research partners 611 00:32:08,733 --> 00:32:11,035 at the weizmann institute 612 00:32:11,036 --> 00:32:14,105 to hack into the minds of sleeping test subjects 613 00:32:14,106 --> 00:32:15,973 using odors. 614 00:32:15,974 --> 00:32:18,710 They hook a test subject up to a machine 615 00:32:18,711 --> 00:32:22,646 that can produce a wide variety of sense 616 00:32:22,647 --> 00:32:26,352 and then measure how deeply the subject breathes. 617 00:32:28,788 --> 00:32:32,356 The subject falls into a deep sleep, 618 00:32:32,357 --> 00:32:36,227 and Ilana and her colleague go to work. 619 00:32:36,228 --> 00:32:39,063 They release a pleasant perfume 620 00:32:39,064 --> 00:32:42,901 and immediately play a high-pitched tone. 621 00:32:42,902 --> 00:32:44,470 [ High-pitched tone plays ] 622 00:32:46,872 --> 00:32:50,142 Later, they release the smell of rotting fish... 623 00:32:53,612 --> 00:32:56,113 And play a low-pitched tone. 624 00:32:56,114 --> 00:32:58,750 [ Low-pitched tone plays ] 625 00:32:58,751 --> 00:33:03,789 The process repeats throughout the night until morning arrives. 626 00:33:09,428 --> 00:33:13,998 Hairston: So, we just got our participant out of bed, 627 00:33:13,999 --> 00:33:16,000 and he's not hearing or smelling anything, 628 00:33:16,001 --> 00:33:19,571 and we're gonna present the tones alone without the smells 629 00:33:19,572 --> 00:33:21,940 to see if he responds to the tones. 630 00:33:21,941 --> 00:33:24,775 So, now we're just watching him breathing. 631 00:33:24,776 --> 00:33:27,912 Freeman: The subject had no conscious awareness 632 00:33:27,913 --> 00:33:30,414 of the odors presented throughout the night 633 00:33:30,415 --> 00:33:32,916 and has no memory of them now, 634 00:33:32,917 --> 00:33:34,485 but Ilana wants to see 635 00:33:34,486 --> 00:33:36,653 if his breathing patterns reveal 636 00:33:36,654 --> 00:33:39,757 an unconscious, visceral reaction 637 00:33:39,758 --> 00:33:42,560 to the high and low tones. 638 00:33:42,561 --> 00:33:45,630 She first plays the tone linked to the perfume. 639 00:33:45,631 --> 00:33:47,398 [ High-pitched tone plays ] 640 00:33:47,399 --> 00:33:50,501 The inhale was much bigger and wider 641 00:33:50,502 --> 00:33:54,104 compared to his normal inhales. 642 00:33:54,105 --> 00:33:56,708 We paired this tone with a pleasant odor. 643 00:33:56,709 --> 00:33:59,276 Then she plays the low-pitched tone, 644 00:33:59,277 --> 00:34:02,379 the one that was paired with the foul stench. 645 00:34:02,380 --> 00:34:04,749 [ Low-pitched tone plays ] 646 00:34:04,750 --> 00:34:07,785 Again, you can see the trigger of the tone, 647 00:34:07,786 --> 00:34:09,821 and he's literally holding his breath. 648 00:34:09,822 --> 00:34:12,823 The subject does not smell anything, 649 00:34:12,824 --> 00:34:16,794 but his mind reacts as though he does. 650 00:34:16,795 --> 00:34:19,497 He associates the high-pitched tone 651 00:34:19,498 --> 00:34:22,434 with pleasant, breathable air 652 00:34:22,533 --> 00:34:27,705 and the low-pitched tone with foul, nauseating odors. 653 00:34:27,806 --> 00:34:28,972 The key issue here 654 00:34:28,973 --> 00:34:30,842 is also that he doesn't actually remember anything 655 00:34:30,843 --> 00:34:32,343 that happened during the night. 656 00:34:32,344 --> 00:34:35,113 He's not actually aware that this tone was associated 657 00:34:35,114 --> 00:34:36,981 with a bad smell or a good smell. 658 00:34:36,982 --> 00:34:39,284 He's just responding to the tone 659 00:34:39,285 --> 00:34:42,587 without any knowledge of what we expect him to do. 660 00:34:42,588 --> 00:34:46,424 Ilana believes that this brain-hacking technique 661 00:34:46,425 --> 00:34:52,797 can be refined and used to manipulate any unconscious mind. 662 00:34:52,798 --> 00:34:54,500 Hairston: And then the question is 663 00:34:54,501 --> 00:34:57,268 can we do this with a more subtle paradigm, 664 00:34:57,269 --> 00:34:59,035 like training people during sleep? 665 00:34:59,036 --> 00:35:00,939 And I think the answer would be "Yes." 666 00:35:00,940 --> 00:35:05,076 Freeman: Take, for example, politics. 667 00:35:05,077 --> 00:35:08,112 Your support of one candidate 668 00:35:08,113 --> 00:35:11,282 might seem, to you, to be unswervable. 669 00:35:11,283 --> 00:35:15,153 But while you are sleeping, 670 00:35:15,154 --> 00:35:17,755 scent hackers could train your mind 671 00:35:17,756 --> 00:35:20,391 to associate pleasant or foul odors 672 00:35:20,392 --> 00:35:22,960 with just about any sound, 673 00:35:22,961 --> 00:35:28,632 even the sound of a particular person's voice. 674 00:35:28,633 --> 00:35:31,101 The next time you hear that voice, 675 00:35:31,102 --> 00:35:33,938 your newly-learned subconscious reaction 676 00:35:33,939 --> 00:35:37,843 could turn adulation into disgust. 677 00:35:42,380 --> 00:35:44,749 Hairston: Because odors are emotional, 678 00:35:44,750 --> 00:35:48,352 I think we could modify our emotional responses to stimuli, 679 00:35:48,353 --> 00:35:50,922 so I think you could modify emotional responses 680 00:35:50,923 --> 00:35:53,090 and thereby modify behavior. 681 00:35:53,091 --> 00:35:55,893 Freeman: Someday, 682 00:35:55,894 --> 00:35:59,897 how we react to anything in the world around us 683 00:35:59,898 --> 00:36:04,201 could be manipulated by a brain hacker. 684 00:36:04,202 --> 00:36:08,005 It's a future that may come sooner than you think, 685 00:36:08,006 --> 00:36:10,441 because this scientist 686 00:36:10,442 --> 00:36:14,345 is already building the ultimate brain hack. 687 00:36:14,346 --> 00:36:18,115 His technology could put any thought into our heads 688 00:36:18,116 --> 00:36:20,919 with a flash of light. 689 00:36:23,000 --> 00:36:25,668 Today, we can manipulate human brains 690 00:36:25,669 --> 00:36:29,706 by tampering with the senses, bathing the brain in chemicals, 691 00:36:29,707 --> 00:36:33,576 or by playing psychological mind games. 692 00:36:33,577 --> 00:36:38,815 But all these methods influence the brain from the outside in. 693 00:36:38,816 --> 00:36:40,450 A true mind hack, 694 00:36:40,451 --> 00:36:44,621 one that opens us up for reprogramming of any kind, 695 00:36:44,622 --> 00:36:48,557 may require something more audacious... 696 00:36:48,558 --> 00:36:54,364 Reaching inside a living brain and flicking a switch. 697 00:36:58,302 --> 00:37:03,306 M.I.T. Engineer, physicist, and neuroscientist ed boyden 698 00:37:03,307 --> 00:37:07,877 has spent his career figuring out how complex machines work. 699 00:37:07,878 --> 00:37:12,082 He's now working on the most complex machine of all... 700 00:37:12,083 --> 00:37:15,351 The human brain. 701 00:37:15,352 --> 00:37:18,888 A cubic millimeter of brain tissue has 100,000 cells, 702 00:37:18,889 --> 00:37:21,391 and there are a billion connections between them. 703 00:37:21,392 --> 00:37:23,392 These cells compute using electricity, 704 00:37:23,393 --> 00:37:25,661 and if all these little electrical computers 705 00:37:25,662 --> 00:37:28,197 could be recorded, perturbed, controlled, and analyzed, 706 00:37:28,198 --> 00:37:30,733 then maybe we could understand how the brain computed it 707 00:37:30,734 --> 00:37:32,268 in the same way that computers 708 00:37:32,269 --> 00:37:34,370 are engineered to do all the things that they do 709 00:37:34,371 --> 00:37:36,506 and our phones and on the Internet and so on. 710 00:37:36,507 --> 00:37:38,074 So, if you have a complex system, 711 00:37:38,075 --> 00:37:41,110 whether it's a computer or a city or the economy or a brain, 712 00:37:41,111 --> 00:37:43,913 one of the ways that you can figure out what's going on 713 00:37:43,914 --> 00:37:45,282 is to actually put little inputs into the system 714 00:37:45,283 --> 00:37:46,882 and see what happens. 715 00:37:46,883 --> 00:37:48,718 Freeman: It's easy to test the 716 00:37:48,719 --> 00:37:51,287 components on a computer circuit board, 717 00:37:51,288 --> 00:37:53,756 but brain cells are a little trickier, 718 00:37:53,757 --> 00:37:57,493 so ed set out to find a natural switch 719 00:37:57,494 --> 00:38:01,598 that can turn individual neurons on or off, 720 00:38:01,599 --> 00:38:07,170 and he found one swimming around in a puddle of pond water. 721 00:38:07,171 --> 00:38:10,206 Boyden: This kind of algae actually has this light sensor. 722 00:38:10,207 --> 00:38:12,373 It sits in a little eye spot in the back of the algae, 723 00:38:12,374 --> 00:38:14,610 and basically, these are little light-activated proteins 724 00:38:14,611 --> 00:38:15,846 known as opsins 725 00:38:15,847 --> 00:38:17,914 that sit in the membranes of cells 726 00:38:17,915 --> 00:38:20,884 and serve as photosynthetic or photosensory protein, 727 00:38:20,885 --> 00:38:23,653 and this is a molecule that converts light 728 00:38:23,654 --> 00:38:26,323 into a very specific change in electrical potential, 729 00:38:26,324 --> 00:38:29,392 the exact same kind that occurs in neurons when they're active. 730 00:38:29,393 --> 00:38:33,096 Freeman: Ed and his colleagues extracted from the algae 731 00:38:33,097 --> 00:38:37,867 the genetic code that produces these light-sensitive opsins. 732 00:38:37,868 --> 00:38:41,304 They then inserted this gene into a virus 733 00:38:41,305 --> 00:38:47,210 that could splice itself into the DNA of living brain cells. 734 00:38:47,211 --> 00:38:50,146 Boyden: The neurons in the brain will manufacture the protein 735 00:38:50,147 --> 00:38:52,348 because now the genome has been incorporated 736 00:38:52,349 --> 00:38:53,850 into the nucleus of other cells 737 00:38:53,851 --> 00:38:56,020 and then expressed those proteins all over the membranes, 738 00:38:56,021 --> 00:38:58,287 or boundaries, of those cells. 739 00:38:58,288 --> 00:39:01,424 Freeman: Ed's virus instructs any infected neurons 740 00:39:01,425 --> 00:39:05,161 to build a light-sensitive on/off switch. 741 00:39:05,162 --> 00:39:07,997 With these switches, any brain circuit 742 00:39:07,998 --> 00:39:11,601 from our senses to our emotional state and memories 743 00:39:11,602 --> 00:39:14,336 could be controlled with this. 744 00:39:14,337 --> 00:39:17,640 Boyden: So, this is a laser that we developed here, 745 00:39:17,641 --> 00:39:19,541 which will then split that laser light 746 00:39:19,542 --> 00:39:21,345 out into an array of optical fibers 747 00:39:21,346 --> 00:39:23,479 that we can enter information into the brain 748 00:39:23,480 --> 00:39:25,047 into many different points 749 00:39:25,048 --> 00:39:28,151 that are distributed in a three-dimensional pattern. 750 00:39:28,152 --> 00:39:29,652 The brain doesn't feel pain, 751 00:39:29,653 --> 00:39:32,222 so we can implant little probes into the brain, 752 00:39:32,223 --> 00:39:34,557 deliver light out the end of these probes, 753 00:39:34,558 --> 00:39:37,060 and then we'll turn on or off parts of the brain 754 00:39:37,061 --> 00:39:38,496 just by pulsing this laser, 755 00:39:38,497 --> 00:39:40,731 turning the laser on and off very rapidly. 756 00:39:42,666 --> 00:39:44,234 Freeman: Ed and his colleagues 757 00:39:44,235 --> 00:39:45,967 first put that technology to trial 758 00:39:45,968 --> 00:39:47,003 with animal subjects. 759 00:39:47,004 --> 00:39:50,372 Ed wired his light-sensitive switches 760 00:39:50,373 --> 00:39:55,044 into a mouse's pleasure-reward brain circuits. 761 00:39:55,045 --> 00:39:57,313 We put in an optical fiber into the brain 762 00:39:57,314 --> 00:39:59,883 such that it could deliver light to those cells. 763 00:39:59,884 --> 00:40:01,784 Then we programmed a computer such that 764 00:40:01,785 --> 00:40:04,287 whenever a mouse hooked its nose into a little sensor, 765 00:40:04,288 --> 00:40:05,921 it would get a pulse of light. 766 00:40:05,922 --> 00:40:07,857 Freeman: Each pulse of blue light 767 00:40:07,858 --> 00:40:10,292 activates the same pleasure-reward circuits 768 00:40:10,293 --> 00:40:12,996 that turn on when the rodent eats a piece of food 769 00:40:12,997 --> 00:40:14,730 or finds a mate. 770 00:40:14,731 --> 00:40:18,033 The mouse keeps poking its head into the hole, 771 00:40:18,034 --> 00:40:20,570 convinced that this simple action 772 00:40:20,571 --> 00:40:24,140 is the source of the reward. 773 00:40:24,141 --> 00:40:25,942 Boyden: And so, what we found 774 00:40:25,943 --> 00:40:28,778 was that mice would actually work for light. 775 00:40:28,779 --> 00:40:30,913 They would poke their nose in the little sensor, 776 00:40:30,914 --> 00:40:33,248 get a pulse of light, say, "Hey, that was interesting, " 777 00:40:33,249 --> 00:40:35,051 and then do it over and over again, 778 00:40:35,052 --> 00:40:37,721 basically doing a task in order to get a pulse of light. 779 00:40:37,722 --> 00:40:39,688 And so what this tells us is 780 00:40:39,689 --> 00:40:42,358 that very brief activation of this set of cells 781 00:40:42,359 --> 00:40:43,792 with a pulse of light 782 00:40:43,793 --> 00:40:46,429 is enough to reinforce whatever the animal was doing 783 00:40:46,430 --> 00:40:47,597 just before. 784 00:40:47,598 --> 00:40:51,200 Freeman: Ed has hacked the mind of a mouse 785 00:40:51,201 --> 00:40:53,303 and changed its behavior, 786 00:40:53,304 --> 00:40:56,572 and he believes it won't be long 787 00:40:56,573 --> 00:41:00,577 before we are ready to use the technique on the human brain. 788 00:41:00,578 --> 00:41:03,045 Boyden: Arguably, humans have been hacking the brain 789 00:41:03,046 --> 00:41:04,479 for a very long time, you know. 790 00:41:04,480 --> 00:41:05,582 Beer, coffee... 791 00:41:05,583 --> 00:41:07,850 Those are examples of neurotechnologies 792 00:41:07,851 --> 00:41:10,986 that their main role is to change what the brain does. 793 00:41:10,987 --> 00:41:13,556 Drugs, pharmaceuticals have been very, very impactful 794 00:41:13,557 --> 00:41:15,225 in treating brain disorders, 795 00:41:15,226 --> 00:41:17,226 but if you think about the brain as a circuit, 796 00:41:17,227 --> 00:41:19,394 then a drug that goes throughout the entire brain 797 00:41:19,395 --> 00:41:21,832 is gonna affect circuits that you want to leave intact, 798 00:41:21,833 --> 00:41:23,899 as well as circuits that you want to fix, 799 00:41:23,900 --> 00:41:26,669 and that's where our technologies come into play. 800 00:41:26,670 --> 00:41:29,072 We really can make a subset of those cells 801 00:41:29,073 --> 00:41:31,475 activatable or silenceable with our tools. 802 00:41:33,210 --> 00:41:35,320 Freeman: Ed's technology could be a 803 00:41:35,321 --> 00:41:37,547 cure for the nearly 1 billion people 804 00:41:37,548 --> 00:41:39,883 who suffer from mental illness 805 00:41:39,884 --> 00:41:43,452 by turning off only unhealthy cells. 806 00:41:43,453 --> 00:41:48,024 It would be a revolution in psychiatric medicine, 807 00:41:48,025 --> 00:41:50,827 and one day, it could give us all 808 00:41:50,828 --> 00:41:56,332 complete control of the workings of our brains. 809 00:41:56,333 --> 00:42:01,805 The rewards for hacking into our brains could be momentous. 810 00:42:01,806 --> 00:42:05,407 Mental diseases could be eliminated. 811 00:42:05,408 --> 00:42:09,044 We could unlock the highest levels of talent, 812 00:42:09,045 --> 00:42:13,415 and we could truly understand what another person feels. 813 00:42:13,416 --> 00:42:17,553 But there is a dark side to this technology. 814 00:42:17,554 --> 00:42:19,922 We could be creating a future 815 00:42:19,923 --> 00:42:23,159 where no one is sure of who they are, 816 00:42:23,160 --> 00:42:26,329 no secrets could ever be safe, 817 00:42:26,330 --> 00:42:31,835 and where we might all lose our minds to brain hackers. 65325

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