1 00:00:00,040 --> 00:00:02,460 The following content is provided under a Creative 2 00:00:02,460 --> 00:00:03,870 Commons license. 3 00:00:03,870 --> 00:00:06,910 Your support will help MIT OpenCourseWare continue to 4 00:00:06,910 --> 00:00:10,560 offer high quality educational resources for free. 5 00:00:10,560 --> 00:00:13,460 To make a donation, or view additional materials from 6 00:00:13,460 --> 00:00:19,290 hundreds of MIT courses, visit MIT OpenCourseWare, at 7 00:00:19,290 --> 00:00:20,540 ocw.mit.edu. 8 00:00:29,330 --> 00:00:30,580 PROFESSOR: Good afternoon. 9 00:00:32,560 --> 00:00:36,930 In the last lecture we talked about the remarkable human 10 00:00:36,930 --> 00:00:39,937 brain, and how it empowers our thoughts, or feelings, or 11 00:00:39,937 --> 00:00:42,920 desires, or actions in the world, and how we began to 12 00:00:42,920 --> 00:00:46,376 understand this remarkable complexity, or at least grasp 13 00:00:46,376 --> 00:00:47,798 something of the complexity. 14 00:00:47,798 --> 00:00:51,890 How we understand the potential for things like 15 00:00:51,890 --> 00:00:53,570 moral character, and judgments. 16 00:00:53,570 --> 00:00:57,250 The case of Phineas Gage, to produce language, to speak our 17 00:00:57,250 --> 00:01:00,250 feelings and thoughts that's blocked in a patient like 18 00:01:00,250 --> 00:01:03,350 Broca's patient, with Broca's aphasia. 19 00:01:03,350 --> 00:01:05,650 We talked about the fact that split brain patients show us 20 00:01:05,650 --> 00:01:08,550 not only to the left and right hemispheres of the human brain 21 00:01:08,550 --> 00:01:13,130 mediate separate mental abilities, but that they also 22 00:01:13,130 --> 00:01:15,220 seem to have almost independent forms of 23 00:01:15,220 --> 00:01:17,070 consciousness, or they don't have to be 24 00:01:17,070 --> 00:01:18,580 aware of one another. 25 00:01:18,580 --> 00:01:22,670 And so my focus today is to say we would learn from very 26 00:01:22,670 --> 00:01:24,480 unusual clinical cases. 27 00:01:24,480 --> 00:01:27,250 And I'm going to focus today on tools we have to study the 28 00:01:27,250 --> 00:01:29,580 typical human brain. 29 00:01:29,580 --> 00:01:34,860 And what is it that we can do to understand how your brain-- 30 00:01:34,860 --> 00:01:36,060 without having a 31 00:01:36,060 --> 00:01:37,830 hemispherectomy or a big stroke-- 32 00:01:37,830 --> 00:01:40,380 how does it operate, and what are the principles of human 33 00:01:40,380 --> 00:01:44,280 brain function they gave rise to the human mind? 34 00:01:44,280 --> 00:01:46,260 So what are the ways we can learn about the human brain? 35 00:01:46,260 --> 00:01:49,370 And one thing we can't do is when animal researchers can 36 00:01:49,370 --> 00:01:52,510 do, we can't literally go inside the brain except in 37 00:01:52,510 --> 00:01:54,280 very rare clinical situations. 38 00:01:54,280 --> 00:01:58,460 I'll talk about them, but it's a rare source of evidence. 39 00:01:58,460 --> 00:02:00,390 So there's a million ways in which are trying to understand 40 00:02:00,390 --> 00:02:02,190 which part of the brain is which part of the mind, and we 41 00:02:02,190 --> 00:02:07,280 talked about the fact that phronology was a big misstep 42 00:02:07,280 --> 00:02:10,990 in assigning the functions of mental life to different parts 43 00:02:10,990 --> 00:02:11,750 of the brain. 44 00:02:11,750 --> 00:02:13,990 And so we hope we can do a bit better than that. 45 00:02:13,990 --> 00:02:17,030 And I'm going to review with you today some of the core 46 00:02:17,030 --> 00:02:19,620 methods, and there's a number of them 47 00:02:19,620 --> 00:02:20,250 studying the human brain. 48 00:02:20,250 --> 00:02:23,130 The reason there's a number is none of them 49 00:02:23,130 --> 00:02:24,560 are the magic answer. 50 00:02:24,560 --> 00:02:26,470 All of them are limited in their own ways, and we sort of 51 00:02:26,470 --> 00:02:29,630 need all of them to begin to grasp how your 52 00:02:29,630 --> 00:02:32,830 brain makes your mind. 53 00:02:32,830 --> 00:02:35,210 There's three huge ways in which we now have the human 54 00:02:35,210 --> 00:02:36,990 brain organized. 55 00:02:36,990 --> 00:02:40,690 Lesions, injuries to the brain, stimulation when you're 56 00:02:40,690 --> 00:02:42,390 allowed to stimulate the brain-- 57 00:02:42,390 --> 00:02:44,140 rarer, but we'll talk about that. 58 00:02:44,140 --> 00:02:46,330 And the most common, the one you see all the time in books 59 00:02:46,330 --> 00:02:50,360 and magazines, recording, functional MRI, EEG, methods 60 00:02:50,360 --> 00:02:52,750 where we record brain activity, and try to 61 00:02:52,750 --> 00:02:56,800 understand how that relates to the life of the human mind. 62 00:02:56,800 --> 00:02:58,400 And so we're going to go through these things a little 63 00:02:58,400 --> 00:03:00,800 bit and show you how they're applied in some ways that I 64 00:03:00,800 --> 00:03:02,600 hope that you'll find interesting. 65 00:03:02,600 --> 00:03:05,100 We'll come back to many of these things as we go through 66 00:03:05,100 --> 00:03:08,080 the semester, and as we talk about aging, or child 67 00:03:08,080 --> 00:03:11,040 development, or personality, or other 68 00:03:11,040 --> 00:03:13,300 topics, social cognition. 69 00:03:13,300 --> 00:03:15,980 We'll use these tools to understand the brain bases of 70 00:03:15,980 --> 00:03:18,690 those kinds of aspects of our mental lives. 71 00:03:18,690 --> 00:03:20,010 So what's a big injury you can have? 72 00:03:20,010 --> 00:03:23,470 You can have a stroke, where tissue in the brain no longer 73 00:03:23,470 --> 00:03:27,030 receives its vascular supply that it depends on so greatly. 74 00:03:27,030 --> 00:03:29,980 And a lot of different things like hypoxia, lack of oxygen, 75 00:03:29,980 --> 00:03:32,310 the brain is very sensitive to oxygen. 76 00:03:32,310 --> 00:03:35,030 Tumors can grow, you could have degenerative disorders 77 00:03:35,030 --> 00:03:37,120 like Alzheimer's, Huntington's, Parkinson's, and 78 00:03:37,120 --> 00:03:39,190 others, epilepsy. 79 00:03:39,190 --> 00:03:41,010 So there's lots of different ways in which you can end up 80 00:03:41,010 --> 00:03:43,740 with brain injury, and ultimately neuronal death. 81 00:03:46,460 --> 00:03:48,050 What's the strength of this form of evidence? 82 00:03:48,050 --> 00:03:49,940 Well first of all, it's causal. 83 00:03:49,940 --> 00:03:51,880 We've talked about the difference between causal and 84 00:03:51,880 --> 00:03:54,260 correlational sources of evidence, causal ones be more 85 00:03:54,260 --> 00:03:56,980 powerful for scientific explanation. 86 00:03:56,980 --> 00:03:59,100 A certain part of the brain is injured in you no longer can 87 00:03:59,100 --> 00:04:02,180 speak, you change your character, you no longer can 88 00:04:02,180 --> 00:04:03,370 make memories. 89 00:04:03,370 --> 00:04:05,600 We're pretty sure that part of the brain in some way is 90 00:04:05,600 --> 00:04:08,340 required, or causal, for that part of your 91 00:04:08,340 --> 00:04:11,300 mental life to operate. 92 00:04:11,300 --> 00:04:14,090 The deficits you see following brain injuries can be amazing, 93 00:04:14,090 --> 00:04:16,480 we talked about Phineas Gage changing his character, unable 94 00:04:16,480 --> 00:04:18,820 to produce language, unable to make new memories. 95 00:04:18,820 --> 00:04:21,579 We'll talk a little bit about patients with Prosopagnosia, 96 00:04:21,579 --> 00:04:24,110 it's a good big word to go home on spring break and if 97 00:04:24,110 --> 00:04:25,570 your parents ask what have you learned about, you say 98 00:04:25,570 --> 00:04:27,270 Prosopagnosia. 99 00:04:27,270 --> 00:04:29,730 That just means a deficit in recognizing faces. 100 00:04:29,730 --> 00:04:32,310 Patients with Prosopagnosia will be unable to recognize 101 00:04:32,310 --> 00:04:34,540 their own spouse by their face. 102 00:04:34,540 --> 00:04:36,720 They'll recognize it by the voice, by the physical 103 00:04:36,720 --> 00:04:39,780 movements, but not by their face. 104 00:04:39,780 --> 00:04:42,940 We learn amazing things about the brain that until it 105 00:04:42,940 --> 00:04:45,300 happens we didn't know that could happen, what people like 106 00:04:45,300 --> 00:04:46,370 to call counterintuitive. 107 00:04:46,370 --> 00:04:49,020 So we'll talk later in the course in a couple times about 108 00:04:49,020 --> 00:04:52,420 blindsight, patients who say, I see nothing, but their 109 00:04:52,420 --> 00:04:55,850 behavior shows some part of their brain sees something. 110 00:04:55,850 --> 00:04:57,920 We'll talk about category specific deficits where 111 00:04:57,920 --> 00:05:01,900 patients all of the sudden can no longer name living things, 112 00:05:01,900 --> 00:05:04,100 but they can name nonliving things. 113 00:05:04,100 --> 00:05:05,220 So you wouldn't have thought of that if 114 00:05:05,220 --> 00:05:06,730 you didn't see that. 115 00:05:06,730 --> 00:05:08,310 And we get separations in the brain 116 00:05:08,310 --> 00:05:09,090 between different things. 117 00:05:09,090 --> 00:05:11,040 We talked about the difference between the left hemisphere 118 00:05:11,040 --> 00:05:12,840 being important for local features, 119 00:05:12,840 --> 00:05:14,250 the right for global. 120 00:05:14,250 --> 00:05:16,320 The left thinking in terms of functional things in the 121 00:05:16,320 --> 00:05:19,320 world, the right in terms of appearances. 122 00:05:19,320 --> 00:05:20,780 We talked about that already. 123 00:05:20,780 --> 00:05:23,150 We'll talk about other things, the hippocampus is important 124 00:05:23,150 --> 00:05:26,690 for knowing that, knowing a piece of information but the 125 00:05:26,690 --> 00:05:29,170 Basal Ganglia is important for learning how to do things, 126 00:05:29,170 --> 00:05:30,930 mental skills and physical skills. 127 00:05:30,930 --> 00:05:33,070 We'll come back to all of those, it gives us way to 128 00:05:33,070 --> 00:05:34,800 organize things. 129 00:05:34,800 --> 00:05:37,170 Much of our most solid understanding of the human 130 00:05:37,170 --> 00:05:39,320 brain still comes from the history of 131 00:05:39,320 --> 00:05:41,170 neurology and lesions. 132 00:05:41,170 --> 00:05:42,390 But what are its limitations? 133 00:05:42,390 --> 00:05:46,500 First, brain injuries don't follow anatomical boundaries, 134 00:05:46,500 --> 00:05:48,630 they sort of crossover things depending on the injury. 135 00:05:48,630 --> 00:05:51,770 So they're not going to selectively damage one part of 136 00:05:51,770 --> 00:05:53,850 the brain and not touch an adjacent one they could be 137 00:05:53,850 --> 00:05:55,520 doing something different. 138 00:05:55,520 --> 00:05:58,430 People can be variable in their response. 139 00:05:58,430 --> 00:06:01,150 Nearby systems, if you have two things in the brain that 140 00:06:01,150 --> 00:06:04,050 are next door to one another, do quite different things. 141 00:06:04,050 --> 00:06:09,170 Injuries are likely to injure them both, and you will have a 142 00:06:09,170 --> 00:06:10,930 wrong conclusion about the architecture 143 00:06:10,930 --> 00:06:13,280 of the human brain. 144 00:06:13,280 --> 00:06:15,940 When we test a patient and ask them to do things after a 145 00:06:15,940 --> 00:06:18,910 brain injury, we don't really test the part of the brain 146 00:06:18,910 --> 00:06:20,390 that's not there. 147 00:06:20,390 --> 00:06:22,340 We really test a part of the brain that is there, people do 148 00:06:22,340 --> 00:06:23,820 the best they can. 149 00:06:23,820 --> 00:06:26,530 So there's secondary degeneration to an injury, 150 00:06:26,530 --> 00:06:27,930 there's recovery from injury, there's 151 00:06:27,930 --> 00:06:29,010 compensation from an injury. 152 00:06:29,010 --> 00:06:31,650 When you test a patient with a brain injury, you're testing 153 00:06:31,650 --> 00:06:34,970 what the rest of the brain can do in the absence of one of 154 00:06:34,970 --> 00:06:37,820 its companions. 155 00:06:37,820 --> 00:06:39,510 And finally can offer limited views of 156 00:06:39,510 --> 00:06:40,990 normal brain function. 157 00:06:40,990 --> 00:06:43,200 Let me pick one and we'll come back in the course. 158 00:06:43,200 --> 00:06:46,320 We're very interested in variation in people-- 159 00:06:46,320 --> 00:06:47,160 individuality-- 160 00:06:47,160 --> 00:06:49,340 what's the neurology of individuality? 161 00:06:49,340 --> 00:06:52,580 That's very hard to study in lesion cases, because we don't 162 00:06:52,580 --> 00:06:53,490 see enough of a lesion. 163 00:06:53,490 --> 00:06:56,760 we don't have enough Phineas Gages to ask would that injury 164 00:06:56,760 --> 00:07:00,762 look different if you grew up in one culture or another, if 165 00:07:00,762 --> 00:07:03,610 you were outgoing versus shy. 166 00:07:03,610 --> 00:07:05,120 Those kinds of things are very hard to 167 00:07:05,120 --> 00:07:08,260 answer patient by patient. 168 00:07:08,260 --> 00:07:11,080 But we can test large groups of people with imaging and ask 169 00:07:11,080 --> 00:07:12,940 what's the influence of culture on your brain 170 00:07:12,940 --> 00:07:13,860 organization? 171 00:07:13,860 --> 00:07:15,985 What's the influence of personality on how your 172 00:07:15,985 --> 00:07:16,690 brain's organized? 173 00:07:16,690 --> 00:07:19,220 And you'll see later on in the semester evidence about those 174 00:07:19,220 --> 00:07:20,750 sorts of things. 175 00:07:20,750 --> 00:07:25,650 So let's go back to Paul Broca, the neurologist who 176 00:07:25,650 --> 00:07:28,030 they gave a name to Broca's area, because he sought a 177 00:07:28,030 --> 00:07:30,220 patient like this, like [INAUDIBLE]. 178 00:07:30,220 --> 00:07:32,630 That this patient had a big injury in this area could no 179 00:07:32,630 --> 00:07:33,510 longer speak. 180 00:07:33,510 --> 00:07:36,100 And every course you ever take about the brain almost will 181 00:07:36,100 --> 00:07:38,370 include a discussion about Broca's area. 182 00:07:38,370 --> 00:07:41,570 So I'm going to warp your world in a very narrow way, 183 00:07:41,570 --> 00:07:44,330 but maybe a shocking way, and tell you we don't even know 184 00:07:44,330 --> 00:07:46,170 how to think about Broca's area once we get more 185 00:07:46,170 --> 00:07:47,860 scientific than that. 186 00:07:47,860 --> 00:07:50,930 So because this is MIT so we're willing to 187 00:07:50,930 --> 00:07:52,100 tell the truth, OK. 188 00:07:52,100 --> 00:07:54,780 So some years later Nina Dronkers said the following 189 00:07:54,780 --> 00:07:58,150 thing, she studied a large group of patients who had 190 00:07:58,150 --> 00:08:00,170 Broca's aphasia by behavior. 191 00:08:00,170 --> 00:08:03,100 That is they had trouble speaking, but the 192 00:08:03,100 --> 00:08:05,160 comprehension was pretty good. 193 00:08:05,160 --> 00:08:07,660 And then she made maps of their injuries and she 194 00:08:07,660 --> 00:08:10,050 overlaid those maps. 195 00:08:10,050 --> 00:08:14,120 And she said who has Broca's aphasia, and if you have 196 00:08:14,120 --> 00:08:17,520 Broca's aphasia, what's the one part of the brain that 197 00:08:17,520 --> 00:08:20,690 every patient with Broca's aphasia has damage to. 198 00:08:20,690 --> 00:08:21,650 Because these patients-- 199 00:08:21,650 --> 00:08:24,090 what you see on these maps is, some patients have damage 200 00:08:24,090 --> 00:08:25,620 here, or here, or here. 201 00:08:25,620 --> 00:08:29,220 But you line them all up and you say, what's the one spot 202 00:08:29,220 --> 00:08:32,179 that you have to have injured to have Broca's aphasia? 203 00:08:32,179 --> 00:08:35,549 And it's not this area that you saw in the picture, it's 204 00:08:35,549 --> 00:08:38,364 this area, in yellow, an area called the Precentral Gyrus of 205 00:08:38,364 --> 00:08:39,975 the Insula. 206 00:08:39,975 --> 00:08:42,860 The Insula is a fascinating, mysterious little structure-- 207 00:08:42,860 --> 00:08:44,490 you have one on the left, and one on the right-- 208 00:08:44,490 --> 00:08:46,590 that runs along from the temporal lobe, up to the 209 00:08:46,590 --> 00:08:48,230 frontal cortex. 210 00:08:48,230 --> 00:08:51,310 Just a couple years ago there was a paper reporting that 211 00:08:51,310 --> 00:08:54,860 patients who had stroke in posterior insula instantly 212 00:08:54,860 --> 00:08:57,670 gave up smoking, and never wanted to smoke again. 213 00:08:57,670 --> 00:09:00,120 There's huge research efforts to help people quit smoking, 214 00:09:00,120 --> 00:09:04,250 just because it's such a difficult health problem. 215 00:09:04,250 --> 00:09:06,520 Nobody is doing insula lesions to help people 216 00:09:06,520 --> 00:09:07,710 stop smoking, OK. 217 00:09:07,710 --> 00:09:11,090 But it just stopped the smoking, and their desire to 218 00:09:11,090 --> 00:09:13,290 smoke, just like that. 219 00:09:13,290 --> 00:09:15,770 This is now more towards the front of the brain, this is 220 00:09:15,770 --> 00:09:18,730 not what anybody in a book or a course will tell you is 221 00:09:18,730 --> 00:09:20,850 Broca's area, that's out here. 222 00:09:20,850 --> 00:09:23,110 But it turns out this is the hot spot, and you could say, 223 00:09:23,110 --> 00:09:25,230 well what about the original patient? 224 00:09:25,230 --> 00:09:27,530 So kind of creatively Nina Dronkers went back and they 225 00:09:27,530 --> 00:09:31,285 did an MRI of the brain of the deceased original Broca's 226 00:09:31,285 --> 00:09:32,910 aphasic patient. 227 00:09:32,910 --> 00:09:36,150 They still had his brain, they put it in a scanner and they 228 00:09:36,150 --> 00:09:37,870 ran a structural MRI. 229 00:09:37,870 --> 00:09:41,010 And what they found was sure enough he had damage way 230 00:09:41,010 --> 00:09:46,040 inside the exterior limit of this damage, in as well as in 231 00:09:46,040 --> 00:09:48,010 white matter that connects to it. 232 00:09:48,010 --> 00:09:51,740 So even now imaging evidence lets us rediscover what is the 233 00:09:51,740 --> 00:09:54,370 true basis of your ability to speak, or its 234 00:09:54,370 --> 00:09:55,840 vulnerability to injury. 235 00:09:55,840 --> 00:09:57,520 And it turns out not to be exactly what 236 00:09:57,520 --> 00:09:59,300 Broca thought it was. 237 00:09:59,300 --> 00:10:02,750 He saw big lesion and he said, this is the part of matters. 238 00:10:02,750 --> 00:10:04,870 It turns out, as far as we understand, it's a slightly 239 00:10:04,870 --> 00:10:06,700 different part that he thought was just at the 240 00:10:06,700 --> 00:10:08,440 edge and not important. 241 00:10:08,440 --> 00:10:12,050 So we can get better even going back to 150 years of 242 00:10:12,050 --> 00:10:15,590 imaging a brain, we don't have many of those brains around. 243 00:10:15,590 --> 00:10:17,950 Stimulation, so you like to go in the brain is stimulate. 244 00:10:17,950 --> 00:10:20,260 People who do animal work will go in and stimulate a neuron 245 00:10:20,260 --> 00:10:21,860 and see what happens. 246 00:10:21,860 --> 00:10:25,030 It's rare, you only get into the patient's brain when they 247 00:10:25,030 --> 00:10:28,440 have a neurosurgical procedure and they're considering a 248 00:10:28,440 --> 00:10:29,880 resection, or removal of tissue. 249 00:10:29,880 --> 00:10:31,820 You can also do recordings by putting grids on 250 00:10:31,820 --> 00:10:34,260 top of those brains. 251 00:10:34,260 --> 00:10:36,610 And Penfield did famous studies for patients with 252 00:10:36,610 --> 00:10:40,230 epilepsy, where he would stimulate and map things that 253 00:10:40,230 --> 00:10:41,920 contributed a lot to our thinking about the brain. 254 00:10:41,920 --> 00:10:45,720 But that's a rare source of evidence, as you can imagine. 255 00:10:45,720 --> 00:10:47,630 Another one that's much more common-- there's one of these 256 00:10:47,630 --> 00:10:50,340 devices down the street in building 46-- 257 00:10:50,340 --> 00:10:53,660 is Transcranial Magnetic Stimulation, or TMS. 258 00:10:53,660 --> 00:10:56,062 So this is one in which people are allowed ethically, and 259 00:10:56,062 --> 00:10:58,980 responsibly to give you a virtual lesion for a few 260 00:10:58,980 --> 00:11:02,180 moments, if you volunteer to do so. 261 00:11:02,180 --> 00:11:04,990 So they put some sort of wire, there's different 262 00:11:04,990 --> 00:11:08,460 configurations, over your head in a targeted location. 263 00:11:08,460 --> 00:11:10,642 It generates a magnetic field that passes through the skull 264 00:11:10,642 --> 00:11:12,540 and induces a current. 265 00:11:12,540 --> 00:11:15,050 And what happens is the current drives lots 266 00:11:15,050 --> 00:11:16,660 of neurons to fire. 267 00:11:16,660 --> 00:11:19,440 Turns out, this is kind of interesting, if all your 268 00:11:19,440 --> 00:11:22,580 neurons are firing at the same moment, in one sense it's as 269 00:11:22,580 --> 00:11:25,420 if none of them were, because there's no information. 270 00:11:25,420 --> 00:11:26,810 There's a lot of different ways you could think about 271 00:11:26,810 --> 00:11:30,670 that, but for example if on your 300 channel television 272 00:11:30,670 --> 00:11:33,030 you had all the channels on simultaneously on the same 273 00:11:33,030 --> 00:11:35,410 screen, it wouldn't be very easy to watch, 274 00:11:35,410 --> 00:11:36,180 something like that. 275 00:11:36,180 --> 00:11:38,910 All the neurons firing pretty much wipes out the 276 00:11:38,910 --> 00:11:40,460 function of that area. 277 00:11:40,460 --> 00:11:44,580 People do feel a little bit of a physical sensation, if 278 00:11:44,580 --> 00:11:47,360 you're prone to epilepsy it's not a good idea to try this, 279 00:11:47,360 --> 00:11:49,240 so it does require some careful supervision 280 00:11:49,240 --> 00:11:49,930 experimentally. 281 00:11:49,930 --> 00:11:52,270 But you can do this with healthy people, and if for 282 00:11:52,270 --> 00:11:55,480 example you do it on this side of the motor cortex, people 283 00:11:55,480 --> 00:11:57,630 twitch or say they felt somebody touch them. 284 00:11:57,630 --> 00:12:00,220 Nobody touched them, but the part of the brain that codes 285 00:12:00,220 --> 00:12:02,510 for touch just got turned on. 286 00:12:02,510 --> 00:12:05,900 If you put it on the occipital cortex, visual cortex, and you 287 00:12:05,900 --> 00:12:08,220 turn on at a certain moment, you could put a word up and 288 00:12:08,220 --> 00:12:10,690 word down, and the person will say they saw nothing. 289 00:12:10,690 --> 00:12:12,570 You'll make them functionally, cortically 290 00:12:12,570 --> 00:12:14,960 blind for a few moments. 291 00:12:14,960 --> 00:12:17,430 People have done experiments like this to suppress 292 00:12:17,430 --> 00:12:20,140 activity, to enhance activity, sometimes it makes people even 293 00:12:20,140 --> 00:12:22,160 faster, like naming pictures. 294 00:12:22,160 --> 00:12:24,550 And it's also been used there's still experimental 295 00:12:24,550 --> 00:12:26,310 studies of whether it can be helpful for treatments of 296 00:12:26,310 --> 00:12:28,870 neuropsychiatric disorders. 297 00:12:28,870 --> 00:12:31,770 It's not invasive, in a sense of you're not going literally 298 00:12:31,770 --> 00:12:35,620 inside, you have a causal thing because turning the 299 00:12:35,620 --> 00:12:38,290 brain on or off. 300 00:12:38,290 --> 00:12:41,530 It's not very well targeted, it can't go into subcortical 301 00:12:41,530 --> 00:12:45,270 areas, but it's a very interesting tool. 302 00:12:45,270 --> 00:12:48,670 Let's talk about recording brain structure for a moment. 303 00:12:48,670 --> 00:12:50,730 It's really important to separate this concept between 304 00:12:50,730 --> 00:12:53,400 recording structure, which is a picture of anatomy, or 305 00:12:53,400 --> 00:12:56,340 function, which is a picture of physiology. 306 00:12:56,340 --> 00:12:58,880 So there's old ones angiography, and things like 307 00:12:58,880 --> 00:12:59,940 that, I'll show you two. 308 00:12:59,940 --> 00:13:02,410 Computed Tomography, and MR and a really cool measure 309 00:13:02,410 --> 00:13:03,650 called Diffusion Tensor Imaging. 310 00:13:03,650 --> 00:13:05,910 And then, dysfunctional measures, and we'll talk about 311 00:13:05,910 --> 00:13:09,710 those, EEG, PET, fMRI, MEG. 312 00:13:09,710 --> 00:13:11,670 So here's some different images you can 313 00:13:11,670 --> 00:13:12,920 get from the brain. 314 00:13:15,650 --> 00:13:18,120 This is a post-mortem brain, this is a cut brain, here's 315 00:13:18,120 --> 00:13:19,960 the front, here's the back. 316 00:13:19,960 --> 00:13:22,000 If a brain was open in front of you, this is 317 00:13:22,000 --> 00:13:23,620 what you would see. 318 00:13:23,620 --> 00:13:25,890 So here's an MRI, Magnetic Resonance Imaging, and it's 319 00:13:25,890 --> 00:13:29,120 pretty good, and I'll show you some more pictures, in showing 320 00:13:29,120 --> 00:13:30,070 you lots of information. 321 00:13:30,070 --> 00:13:32,700 Not as good as if you were in there, but pretty good. 322 00:13:32,700 --> 00:13:35,120 Here's a CT scan, Computed Tomography. 323 00:13:35,120 --> 00:13:36,840 It's not as good, it's more blurry. 324 00:13:36,840 --> 00:13:40,430 And this thing that looks really sad, it looks like get 325 00:13:40,430 --> 00:13:43,810 your camera to focus, that's actually the quality of the 326 00:13:43,810 --> 00:13:46,040 picture that we see that underlies maybe the most 327 00:13:46,040 --> 00:13:48,290 widely used tool these days for understanding the human 328 00:13:48,290 --> 00:13:50,720 mind and brain, Functional Magnetic Resonance Imaging. 329 00:13:50,720 --> 00:13:52,830 It's a very smudgy picture, but it has some really 330 00:13:52,830 --> 00:13:54,660 interesting properties. 331 00:13:54,660 --> 00:13:56,970 So here's the kind of thing you go into for an MRI, both 332 00:13:56,970 --> 00:13:59,550 structural or functional. 333 00:13:59,550 --> 00:14:03,040 Some of you have almost certainly been participants in 334 00:14:03,040 --> 00:14:04,690 research or experiments, or studies, stick up 335 00:14:04,690 --> 00:14:05,870 your hand if you have. 336 00:14:05,870 --> 00:14:09,930 Oh, a lot of you, OK, so you'll speak up on this, is it 337 00:14:09,930 --> 00:14:12,110 quiet or noisy? 338 00:14:12,110 --> 00:14:17,570 It's super noisy, so you have to have ear plugs in. 339 00:14:17,570 --> 00:14:19,980 And this is why people doing experiments with this 340 00:14:19,980 --> 00:14:22,320 Functional MRI want to do visual studies, because 341 00:14:22,320 --> 00:14:23,300 auditory ones are tricky. 342 00:14:23,300 --> 00:14:26,030 So Tyler, your head TA, likes auditory stuff, it's 10 times 343 00:14:26,030 --> 00:14:27,420 harder to pull off those experiments. 344 00:14:27,420 --> 00:14:29,700 Everybody tries to do visual stuff, so you don't have the 345 00:14:29,700 --> 00:14:30,940 noise problem. 346 00:14:30,940 --> 00:14:33,485 But you get some beautiful pictures, here's Computed 347 00:14:33,485 --> 00:14:35,250 Tomography. 348 00:14:35,250 --> 00:14:38,160 And here's an MRI structural scan from the brain, the 349 00:14:38,160 --> 00:14:39,500 ventricles, here's Basal Ganglia. 350 00:14:42,000 --> 00:14:45,570 With an MRI, beautifully you can see the difference between 351 00:14:45,570 --> 00:14:47,460 white and gray matter. 352 00:14:47,460 --> 00:14:49,080 I'm always impressed that the gray matter is 353 00:14:49,080 --> 00:14:50,520 just this thin ribbon. 354 00:14:50,520 --> 00:14:52,580 Cortex really means bark, it's just like 355 00:14:52,580 --> 00:14:54,860 the bark on our tree. 356 00:14:54,860 --> 00:14:56,600 And when you look at the brain this way, look at how much 357 00:14:56,600 --> 00:14:57,350 white matter there is. 358 00:14:57,350 --> 00:14:59,500 Here's your frontal cortex, look at all that white matter 359 00:14:59,500 --> 00:15:02,490 and then this thin, cortical mantle, or ribbon, or bark. 360 00:15:02,490 --> 00:15:06,070 That's what we think of as the smarts of language, and social 361 00:15:06,070 --> 00:15:07,380 planning, and things like that. 362 00:15:07,380 --> 00:15:10,970 So that's a structural picture. 363 00:15:10,970 --> 00:15:14,370 And then these two pictures are sort of fun. 364 00:15:14,370 --> 00:15:18,750 This is just recorded down the street, we're going to fly 365 00:15:18,750 --> 00:15:32,550 through your brain from one ear to the other. 366 00:15:36,650 --> 00:15:38,940 And you get amazing resolution, it's not the same 367 00:15:38,940 --> 00:15:40,230 thing like being inside the brain. 368 00:15:40,230 --> 00:15:42,890 There's things that you don't see, we know that, 369 00:15:42,890 --> 00:15:43,960 but you see a lot. 370 00:15:43,960 --> 00:15:45,210 Isn't that cool? 371 00:15:49,770 --> 00:15:52,640 Let's examine what you can see now. 372 00:15:52,640 --> 00:15:55,120 Only about 40 years ago, you would have to have a person 373 00:15:55,120 --> 00:15:55,970 die to see this. 374 00:15:55,970 --> 00:15:57,540 This is a patient with Huntington's disease, we'll 375 00:15:57,540 --> 00:15:59,630 come back and talk about that disorder. 376 00:15:59,630 --> 00:16:01,770 Here's a healthy person, top of the brain. 377 00:16:01,770 --> 00:16:04,290 This is the caudate here, part of the Basal Ganglia. 378 00:16:04,290 --> 00:16:06,870 And you could see in a patient who has passed away that part 379 00:16:06,870 --> 00:16:08,850 of the brain is completely withered away in 380 00:16:08,850 --> 00:16:11,720 Huntington's disease. 381 00:16:11,720 --> 00:16:13,530 You would have to wait until person passed away to see 382 00:16:13,530 --> 00:16:15,960 something like that. 383 00:16:15,960 --> 00:16:17,640 Here's a healthy person top of the brain, 384 00:16:17,640 --> 00:16:19,140 again lining the ventricle. 385 00:16:19,140 --> 00:16:20,310 This is the caudate. 386 00:16:20,310 --> 00:16:22,160 And here in a living Huntington's patients you can 387 00:16:22,160 --> 00:16:23,490 see the great withering away. 388 00:16:23,490 --> 00:16:26,110 Some of cortex 2 in later stage of disease, but 389 00:16:26,110 --> 00:16:27,360 especially in the Basal Ganglia. 390 00:16:29,950 --> 00:16:33,470 Here's a healthy older person, about 70 years of age, top of 391 00:16:33,470 --> 00:16:35,940 the brain, bottom of the brain, the ventricle. 392 00:16:35,940 --> 00:16:38,700 Here's on the left and right of the hippocampus, the 393 00:16:38,700 --> 00:16:41,900 structure we'll talk about, without which you can cannot 394 00:16:41,900 --> 00:16:44,870 learn any new fact, or remember any 395 00:16:44,870 --> 00:16:47,220 event in your life. 396 00:16:47,220 --> 00:16:51,090 So powerful for almost every sense of learning. 397 00:16:51,090 --> 00:16:53,990 And look what happens the structure in the same aged 398 00:16:53,990 --> 00:16:56,510 patient with Alzheimer's disease. 399 00:16:56,510 --> 00:16:59,120 It's virtually gone, it's greatly weathered. 400 00:16:59,120 --> 00:17:02,190 You see it's much wider here, because the tissue's greatly 401 00:17:02,190 --> 00:17:05,290 shrunk in the Alzheimer's patient. 402 00:17:05,290 --> 00:17:08,599 So we can see these kinds of changes in living people, for 403 00:17:08,599 --> 00:17:12,089 both research purposes and clinical purposes. 404 00:17:12,089 --> 00:17:14,530 Here's one that's more cheerful, and more reflecting 405 00:17:14,530 --> 00:17:15,740 your experience. 406 00:17:15,740 --> 00:17:20,400 Here are studies of brain changes from age four to 21. 407 00:17:20,400 --> 00:17:22,700 So they follow a large number of people at NIH 408 00:17:22,700 --> 00:17:24,890 from age four to 21. 409 00:17:24,890 --> 00:17:27,940 And what this shows is this color coding is the thickness 410 00:17:27,940 --> 00:17:29,360 of the cortex. 411 00:17:29,360 --> 00:17:32,810 And you might imagine that as you get older, and smarter and 412 00:17:32,810 --> 00:17:34,890 go through grade school, and middle school, and high 413 00:17:34,890 --> 00:17:37,340 school, and MIT college, and as you head towards grad 414 00:17:37,340 --> 00:17:38,960 school, your brain will get thicker, and 415 00:17:38,960 --> 00:17:40,290 thicker with cortex. 416 00:17:40,290 --> 00:17:42,050 It's exactly the opposite. 417 00:17:42,050 --> 00:17:43,950 Ever since you were about five years old, you've been 418 00:17:43,950 --> 00:17:48,280 shedding neurons by the millions, and connections 419 00:17:48,280 --> 00:17:50,980 among them by the trillions. 420 00:17:50,980 --> 00:17:52,530 And you're still going to do that until your 421 00:17:52,530 --> 00:17:54,630 probably about 22 or 23. 422 00:17:54,630 --> 00:17:57,930 Then you peak, and you decline and become faculty members. 423 00:18:01,490 --> 00:18:04,450 But that's really interesting, we'll come back to this, that 424 00:18:04,450 --> 00:18:07,750 what happens as your brain get smart, experienced, 425 00:18:07,750 --> 00:18:10,820 knowledgeable, all the differences between you now, 426 00:18:10,820 --> 00:18:14,390 if you're 17, 18, 19, 20, and when you were four, it all 427 00:18:14,390 --> 00:18:17,970 goes with your cortex getting thinner. 428 00:18:17,970 --> 00:18:19,690 And we'll come back to that and how people think about 429 00:18:19,690 --> 00:18:23,240 that, but let's see if I can get this next movie to run. 430 00:18:23,240 --> 00:18:24,930 There's also an ordering-- and we'll come back this but I 431 00:18:24,930 --> 00:18:26,640 want to show you this movie. 432 00:18:26,640 --> 00:18:29,090 So the more blue you are, the thinner you are, the more 433 00:18:29,090 --> 00:18:31,670 advanced you are in terms of ultimate young adult 434 00:18:31,670 --> 00:18:32,900 development. 435 00:18:32,900 --> 00:18:35,740 Here's visual cortex, vision coming in. 436 00:18:35,740 --> 00:18:39,150 This is Somatomotor Cortex, how you feel, your body, and 437 00:18:39,150 --> 00:18:40,580 how you move yourself. 438 00:18:40,580 --> 00:18:44,200 And what you see is, as you go from age four to 21, the blue 439 00:18:44,200 --> 00:18:49,960 spreads, that spreading is your brain maturing in higher 440 00:18:49,960 --> 00:18:51,510 thought areas. 441 00:18:51,510 --> 00:18:55,755 So we're going to review your life on average right now, 442 00:18:55,755 --> 00:18:57,005 here you go. 443 00:19:03,150 --> 00:19:06,020 And now you're ready to graduate. 444 00:19:06,020 --> 00:19:09,540 It's kind of an amazing story of fantastic brain changes 445 00:19:09,540 --> 00:19:12,240 that move you from what you could do and not do at four, 446 00:19:12,240 --> 00:19:15,910 to what you can do and not do at age 21. 447 00:19:15,910 --> 00:19:18,600 And we couldn't see these things, we couldn't begin to 448 00:19:18,600 --> 00:19:21,230 see these things, until just a few years ago in any 449 00:19:21,230 --> 00:19:22,360 scientific sense. 450 00:19:22,360 --> 00:19:24,990 All these things are like miraculous sources of 451 00:19:24,990 --> 00:19:27,540 information. 452 00:19:27,540 --> 00:19:29,080 So let's pick another thing, and we'll tie 453 00:19:29,080 --> 00:19:30,620 it to school work. 454 00:19:30,620 --> 00:19:32,300 Here's the structure we said, the hippocampus. 455 00:19:32,300 --> 00:19:36,790 So important for the formation of new memories on an everyday 456 00:19:36,790 --> 00:19:40,210 basis, everything that's important and that you learn. 457 00:19:40,210 --> 00:19:43,060 So here's a fun study they took, and as you hear it, 458 00:19:43,060 --> 00:19:46,130 think about its scientific limitation, but it's fun as 459 00:19:46,130 --> 00:19:47,740 students to think about. 460 00:19:47,740 --> 00:19:51,900 They looked at students in medical school in Germany. 461 00:19:51,900 --> 00:19:55,080 They looked at the measure of an anatomic thickness of the 462 00:19:55,080 --> 00:19:59,790 hippocampus before and after they studied like crazy for a 463 00:19:59,790 --> 00:20:02,600 huge exam over some number of periods. 464 00:20:06,330 --> 00:20:08,260 This is the difference between the two, and what they're 465 00:20:08,260 --> 00:20:11,650 showing you is that as you study, your hippocampus got 466 00:20:11,650 --> 00:20:13,980 thicker as you crammed for your test. 467 00:20:13,980 --> 00:20:16,350 So will there be a day where instead of having to give you 468 00:20:16,350 --> 00:20:17,910 tests we could just measure the thickness of your 469 00:20:17,910 --> 00:20:19,910 hippocampus to know how much you studied, and you could 470 00:20:19,910 --> 00:20:22,520 just zoom in and out of a scanner, I don't know. 471 00:20:22,520 --> 00:20:24,660 But one cool thing about it is it's showing you that we can 472 00:20:24,660 --> 00:20:27,950 see structural changes not just on a giant scale from 473 00:20:27,950 --> 00:20:30,990 when you're four to 21, but from some number of months of 474 00:20:30,990 --> 00:20:34,770 experience, we can see a physical change in your brain. 475 00:20:34,770 --> 00:20:37,100 Now that's trivial for animal researchers, they can show 476 00:20:37,100 --> 00:20:40,410 amazing things in seconds, but you see the human brain 477 00:20:40,410 --> 00:20:41,740 physically changing. 478 00:20:41,740 --> 00:20:43,870 So let's take a look at another one, slightly more 479 00:20:43,870 --> 00:20:47,590 controlled, we'll look at two more examples. 480 00:20:47,590 --> 00:20:50,850 London taxi cab drivers. 481 00:20:50,850 --> 00:20:52,650 If you've travelled in various cities, and have gone in 482 00:20:52,650 --> 00:20:55,370 various taxis, you may have had better or worse 483 00:20:55,370 --> 00:20:57,630 experiences whether the taxi driver knows where he or she 484 00:20:57,630 --> 00:20:58,720 is going exactly. 485 00:20:58,720 --> 00:21:02,120 London is famous for having a very high code, taxi drivers 486 00:21:02,120 --> 00:21:07,650 have to take big exams to get their official taxi license, 487 00:21:07,650 --> 00:21:09,980 they create a very demanding thing. 488 00:21:09,980 --> 00:21:13,020 And when they ask this in the hippocampus if you learn lots 489 00:21:13,020 --> 00:21:16,315 of routes, if you know tons of routes in London, what happens 490 00:21:16,315 --> 00:21:18,100 to the hippocampus as it's memorizing all 491 00:21:18,100 --> 00:21:19,170 these special routes? 492 00:21:19,170 --> 00:21:23,180 And what they saw, that taxi drivers had bigger hippocampi, 493 00:21:23,180 --> 00:21:27,660 and the longer they drove, the bigger it was. 494 00:21:27,660 --> 00:21:28,830 So is this a causal or 495 00:21:28,830 --> 00:21:30,085 correlational source of evidence? 496 00:21:33,050 --> 00:21:35,490 It's correlational right? 497 00:21:35,490 --> 00:21:37,560 So let's start with this, they have bigger hippocampi, and 498 00:21:37,560 --> 00:21:40,870 now maybe that's simply because, what? 499 00:21:40,870 --> 00:21:43,300 Maybe somebody who has an awesome hippocampus is ready 500 00:21:43,300 --> 00:21:44,940 to go to be a taxi driver. 501 00:21:44,940 --> 00:21:48,630 Maybe they pass the test, and the one who got lost all the 502 00:21:48,630 --> 00:21:50,940 time, and was driving to the wrong airport and stuff, small 503 00:21:50,940 --> 00:21:53,080 hippocampus, never became a taxi driver. 504 00:21:53,080 --> 00:21:56,290 So the size of the hippocampus is the cause of your success, 505 00:21:56,290 --> 00:21:57,660 not the consequence. 506 00:21:57,660 --> 00:22:00,560 Because the longer you drove, the bigger it got, that kind 507 00:22:00,560 --> 00:22:01,960 of goes with that. 508 00:22:01,960 --> 00:22:05,620 But you could do a causal experiment this way. 509 00:22:05,620 --> 00:22:08,280 They taught people to juggle three balls, they practiced 510 00:22:08,280 --> 00:22:10,470 every day for three months. 511 00:22:10,470 --> 00:22:12,760 Three months juggling every day. 512 00:22:12,760 --> 00:22:15,413 What you see in yellow are parts of the brain-- that's a 513 00:22:15,413 --> 00:22:17,400 statistical map-- 514 00:22:17,400 --> 00:22:21,260 parts of the brain that significantly got thicker in 515 00:22:21,260 --> 00:22:22,295 three months of practice. 516 00:22:22,295 --> 00:22:24,730 So they could compare directly before and after, it's a 517 00:22:24,730 --> 00:22:27,050 causal experiment. 518 00:22:27,050 --> 00:22:30,730 And these are areas that are involved in the visual motion, 519 00:22:30,730 --> 00:22:34,190 and it makes sense that areas involved in visual motion 520 00:22:34,190 --> 00:22:35,140 would somehow change. 521 00:22:35,140 --> 00:22:37,490 But the fact that we can see three months of experience 522 00:22:37,490 --> 00:22:40,340 change the structure of your brain, it's kind of remarkable 523 00:22:40,340 --> 00:22:42,580 in they way that we can measure and scientifically 524 00:22:42,580 --> 00:22:43,760 scrutinize. 525 00:22:43,760 --> 00:22:46,550 You might be curious if you did three months of this and 526 00:22:46,550 --> 00:22:48,150 you were a pretty good juggler, you're impressing 527 00:22:48,150 --> 00:22:51,700 your friends at parties, your brain scan is different. 528 00:22:51,700 --> 00:22:52,790 What do you think happened-- 529 00:22:52,790 --> 00:22:55,070 they followed these people up-- after the juggling 530 00:22:55,070 --> 00:22:57,150 requirements stopped? 531 00:22:57,150 --> 00:22:59,490 They kind of stop, most of the people, they were too busy. 532 00:22:59,490 --> 00:23:01,300 They would show off here and there, but that was it. 533 00:23:01,300 --> 00:23:04,060 They measured their brain's again about six months later, 534 00:23:04,060 --> 00:23:05,890 and this change was gone. 535 00:23:05,890 --> 00:23:09,210 It came in, and it went out with the activity, it's 536 00:23:09,210 --> 00:23:10,210 activity dependent. 537 00:23:10,210 --> 00:23:13,710 So depending on what you do, you could think about every 538 00:23:13,710 --> 00:23:16,090 activity you do-- mental and physical that you do-- is 539 00:23:16,090 --> 00:23:18,710 constantly slightly changing your brain. 540 00:23:18,710 --> 00:23:21,440 And if you do a lot of it, you're fundamentally changing 541 00:23:21,440 --> 00:23:22,510 it like in these individuals. 542 00:23:22,510 --> 00:23:25,320 But if you stop doing it you go right back to where you 543 00:23:25,320 --> 00:23:28,460 were, because you're going to be doing something else. 544 00:23:28,460 --> 00:23:31,210 And another fun measure that's kind of beautiful and 545 00:23:31,210 --> 00:23:33,110 intriguing is Diffusion Tensor Imaging. 546 00:23:33,110 --> 00:23:35,020 Now every [INAUDIBLE] we talked about so far has been 547 00:23:35,020 --> 00:23:37,470 gray matter of the brain, the neurons and then the 548 00:23:37,470 --> 00:23:38,820 circuits they form. 549 00:23:38,820 --> 00:23:40,310 We're going to turn to white matter, which is the 550 00:23:40,310 --> 00:23:44,720 myelinated axons that are the super conducting 551 00:23:44,720 --> 00:23:46,750 highways of the brain. 552 00:23:46,750 --> 00:23:49,270 And what Diffusion Tensor Imaging does, it shows you 553 00:23:49,270 --> 00:23:51,100 something about the organization of that white 554 00:23:51,100 --> 00:23:55,360 matter, measuring directly the movement of water at very, 555 00:23:55,360 --> 00:23:58,850 very tiny distances. 556 00:23:58,850 --> 00:24:01,740 This is a cross-section of a myelinated nerve fiber. 557 00:24:01,740 --> 00:24:04,170 Those are the fibers that are covered with white matter that 558 00:24:04,170 --> 00:24:05,550 have to go some distance. 559 00:24:05,550 --> 00:24:08,470 And the myelin protects the quality and speed of that 560 00:24:08,470 --> 00:24:10,310 signal through your brain. 561 00:24:10,310 --> 00:24:13,000 And you could see at the level of, if you're a tiny, tiny 562 00:24:13,000 --> 00:24:16,570 drop of water, or smaller than that, this is a pretty big 563 00:24:16,570 --> 00:24:18,670 bump in the road. 564 00:24:18,670 --> 00:24:21,770 So imagine you're a little drop of water moving a little 565 00:24:21,770 --> 00:24:24,530 bit, and you bump up against the myelin, you go oh, can't 566 00:24:24,530 --> 00:24:26,200 go that way, and you go back this way, and 567 00:24:26,200 --> 00:24:27,005 you go with the flow. 568 00:24:27,005 --> 00:24:30,180 You go parallel with a myelin, it's hard to cross it at that 569 00:24:30,180 --> 00:24:32,000 microscopic scale. 570 00:24:32,000 --> 00:24:35,360 But we can measure that movement in areas where it's 571 00:24:35,360 --> 00:24:39,290 highly constrained, and that's a property of the water. 572 00:24:39,290 --> 00:24:41,980 Here cerebral spinal fluid, things can go anywhere. 573 00:24:41,980 --> 00:24:43,970 Here's where there's a lot of white matter, and the water 574 00:24:43,970 --> 00:24:46,930 tends to flow along parallel with the white matter, just 575 00:24:46,930 --> 00:24:49,960 for physical reasons it can't cross it over. 576 00:24:49,960 --> 00:24:54,530 And here for example, is a statistical map comparing this 577 00:24:54,530 --> 00:24:57,760 measure of white matter organization between adults, 578 00:24:57,760 --> 00:25:01,780 who either in their childhood had a diagnosis of dyslexia, 579 00:25:01,780 --> 00:25:04,060 reading was difficult for these individuals. 580 00:25:04,060 --> 00:25:07,370 Or people who typical reading development, where you learned 581 00:25:07,370 --> 00:25:09,440 to read and wasn't particularly difficult. 582 00:25:09,440 --> 00:25:11,610 And you can see that in this area around the Temporal 583 00:25:11,610 --> 00:25:14,670 Parietal Cortex, there's a significant difference. 584 00:25:14,670 --> 00:25:17,400 But we can do one more thing. 585 00:25:17,400 --> 00:25:20,540 These are reading scores this way, this is the measure of 586 00:25:20,540 --> 00:25:22,110 the white matter organization from the 587 00:25:22,110 --> 00:25:23,970 Diffusion Tensor Imaging. 588 00:25:23,970 --> 00:25:26,630 Each of these as an individual person now. 589 00:25:26,630 --> 00:25:29,380 So the open dots are the people who had typical reading 590 00:25:29,380 --> 00:25:30,940 development. 591 00:25:30,940 --> 00:25:34,550 The filled dots are the people who had poor development, and 592 00:25:34,550 --> 00:25:36,600 you can see it's pretty continuous. 593 00:25:36,600 --> 00:25:38,950 Even in the people with the open circles who never had a 594 00:25:38,950 --> 00:25:42,280 problem, the better they read, the more the 595 00:25:42,280 --> 00:25:44,930 organization is here. 596 00:25:44,930 --> 00:25:46,570 So this is not just the difference between good and 597 00:25:46,570 --> 00:25:50,040 bad readers, it's a difference between really good readers, 598 00:25:50,040 --> 00:25:52,710 and medium readers, and poor readers, right, continuous. 599 00:25:52,710 --> 00:25:54,000 So now, cause or effect? 600 00:25:57,630 --> 00:26:00,180 Were those of you who at three, who had awesome myelin, 601 00:26:00,180 --> 00:26:01,480 were you going, reading's a snap. 602 00:26:01,480 --> 00:26:04,880 I love this stuff, where's War and Peace, mom? 603 00:26:04,880 --> 00:26:09,960 Or, were you like the jugglers, and you were reading 604 00:26:09,960 --> 00:26:12,210 a lot, and you were exercising this part of the brain, and 605 00:26:12,210 --> 00:26:15,240 altered its physical structure. 606 00:26:15,240 --> 00:26:17,200 And the answer is we don't know. 607 00:26:17,200 --> 00:26:20,080 How could we know? 608 00:26:20,080 --> 00:26:21,330 How could we know? 609 00:26:23,350 --> 00:26:26,400 If you were scientists and were given a pot of money to 610 00:26:26,400 --> 00:26:30,010 do this, how could you know? 611 00:26:30,010 --> 00:26:30,670 Well-- 612 00:26:30,670 --> 00:26:31,679 yeah? 613 00:26:31,679 --> 00:26:36,170 AUDIENCE: Track the entire lives of multiple people. 614 00:26:36,170 --> 00:26:37,590 PROFESSOR: Yeah, do a longitudinal study and start 615 00:26:37,590 --> 00:26:40,190 like, before people read. 616 00:26:40,190 --> 00:26:42,950 And you could see is it different then? 617 00:26:42,950 --> 00:26:47,130 Are we born to be big readers, or by being big readers do we 618 00:26:47,130 --> 00:26:50,740 alter the architecture our brain. 619 00:26:50,740 --> 00:26:52,510 What's the effort, and what's the talent, or what's the 620 00:26:52,510 --> 00:26:56,350 predisposition at birth, and what's the time you put in 621 00:26:56,350 --> 00:26:57,010 creating this part. 622 00:26:57,010 --> 00:27:00,500 We don't know that yet, but we have a place to look at that. 623 00:27:00,500 --> 00:27:02,940 And then you can create these kinds of beautiful pictures, 624 00:27:02,940 --> 00:27:04,240 and I'll say a word about this. 625 00:27:04,240 --> 00:27:06,350 So this is an individual person's white matter 626 00:27:06,350 --> 00:27:07,910 organization. 627 00:27:07,910 --> 00:27:10,150 So we could take this picture of you, or anybody you know 628 00:27:10,150 --> 00:27:12,870 who wants to go in a scanner. 629 00:27:12,870 --> 00:27:16,450 And what's color coded here in blue are fibers that are 630 00:27:16,450 --> 00:27:19,690 running up or down, we can't tell with the fibers which 631 00:27:19,690 --> 00:27:22,110 direction they're going, but we can tell other 632 00:27:22,110 --> 00:27:22,850 orientations. 633 00:27:22,850 --> 00:27:26,150 Up and down, left and right in red, up and down in blue, and 634 00:27:26,150 --> 00:27:27,400 green is front to back. 635 00:27:31,470 --> 00:27:32,320 Pretty cool, huh? 636 00:27:32,320 --> 00:27:35,146 I can tell you that I'll say a word about this. 637 00:27:40,750 --> 00:27:42,000 Should we do that again? 638 00:27:44,480 --> 00:27:47,180 I like it, but I work in this area. 639 00:27:49,700 --> 00:27:52,210 This is fantastic, this is an individual person's white 640 00:27:52,210 --> 00:27:54,050 matter organization. 641 00:27:54,050 --> 00:27:56,750 As information is flowing around in your mind, here's 642 00:27:56,750 --> 00:27:59,520 the paths that it's flowing around in as you just do 643 00:27:59,520 --> 00:28:01,790 anything that's interesting in your feelings 644 00:28:01,790 --> 00:28:02,440 or thoughts or anything. 645 00:28:02,440 --> 00:28:03,250 It's fantastic. 646 00:28:03,250 --> 00:28:08,840 I can tell you that the algorithms that are used to 647 00:28:08,840 --> 00:28:10,450 create these maps, there's some debate 648 00:28:10,450 --> 00:28:11,880 about the better ones. 649 00:28:11,880 --> 00:28:14,990 So the last steps of this are a bit debated, and a bit 650 00:28:14,990 --> 00:28:19,570 depending on how cool you are as a visual engineer. 651 00:28:19,570 --> 00:28:21,310 But there's a lot of things that's right about Diffusion 652 00:28:21,310 --> 00:28:24,340 Tensor Imaging, there's a lot of things that 653 00:28:24,340 --> 00:28:25,590 are right about it. 654 00:28:28,280 --> 00:28:32,870 Function, so most of all we're interested in structure, not 655 00:28:32,870 --> 00:28:36,510 just for itself, but how is it makes your mind do the things 656 00:28:36,510 --> 00:28:37,490 you could do. 657 00:28:37,490 --> 00:28:39,290 And when we think about different functional measures 658 00:28:39,290 --> 00:28:40,930 that are available to neuroscientists or 659 00:28:40,930 --> 00:28:44,047 psychologists, we often think in two dimensions, Spatial 660 00:28:44,047 --> 00:28:47,100 Resolution, and Temporal Resolution. 661 00:28:47,100 --> 00:28:51,370 How precise are we where we are, and what's the time scale 662 00:28:51,370 --> 00:28:54,150 that we're measuring in, milliseconds, are we averaging 663 00:28:54,150 --> 00:28:56,460 over many seconds, many hours. 664 00:28:56,460 --> 00:29:00,020 We know mental operations, roughly speaking, occur at the 665 00:29:00,020 --> 00:29:02,640 millisecond level, or maybe 10 milliseconds. 666 00:29:02,640 --> 00:29:05,260 There's no answer to that, but we know lots of things happen 667 00:29:05,260 --> 00:29:07,020 that fast in the mind. 668 00:29:07,020 --> 00:29:10,410 So if you look at this here you can see that, for example, 669 00:29:10,410 --> 00:29:12,880 if you're in animal work, looking at size, you can get 670 00:29:12,880 --> 00:29:14,730 down to the Synapse or the Dendrite. 671 00:29:14,730 --> 00:29:17,980 We can't touch that in humans, we can't touch 672 00:29:17,980 --> 00:29:19,660 that cellular stuff. 673 00:29:19,660 --> 00:29:23,010 And it's not until we get up to here, which is like big 674 00:29:23,010 --> 00:29:26,720 patches of the brain, that we can state things about people. 675 00:29:26,720 --> 00:29:28,530 That's why it's always going to be fundamental in 676 00:29:28,530 --> 00:29:31,590 neuroscience to link the human work to the animal work, 677 00:29:31,590 --> 00:29:34,620 because we can't get to the neurons or anything like that 678 00:29:34,620 --> 00:29:37,210 in a person almost ever. 679 00:29:37,210 --> 00:29:38,900 That has to come from animal work, where you can do 680 00:29:38,900 --> 00:29:40,030 invasive work. 681 00:29:40,030 --> 00:29:41,630 So we have to look at a pretty big patches 682 00:29:41,630 --> 00:29:42,830 of the human brain. 683 00:29:42,830 --> 00:29:44,040 How about time? 684 00:29:44,040 --> 00:29:46,950 Well, we can get down to milliseconds in time in the 685 00:29:46,950 --> 00:29:47,910 human brain. 686 00:29:47,910 --> 00:29:51,190 Functional things like PET and MRI are here and in the order 687 00:29:51,190 --> 00:29:53,850 of multiple seconds, I'll come back to this. 688 00:29:53,850 --> 00:29:55,360 But you can see all these things have strengths. 689 00:29:55,360 --> 00:29:59,690 Now you don't always want to be down to a single synapse, 690 00:29:59,690 --> 00:30:01,870 it's not clear that we would understand much of the 691 00:30:01,870 --> 00:30:04,500 organization of the brain at the level of the synapse. 692 00:30:04,500 --> 00:30:06,510 There's things happening in the synapse, but a thing like 693 00:30:06,510 --> 00:30:08,650 knowledge, or love, or something like that probably 694 00:30:08,650 --> 00:30:11,240 we can't study at the level of the synapse. 695 00:30:11,240 --> 00:30:12,590 Effectively, yet. 696 00:30:12,590 --> 00:30:15,290 Bigger units are probably more interpretable. 697 00:30:15,290 --> 00:30:18,180 So here's a fun one, EEG's, Electroencephalography. 698 00:30:18,180 --> 00:30:22,370 So they put on your head some sort of a cap with electrodes, 699 00:30:22,370 --> 00:30:25,760 and they measure changes in electrical activity that are 700 00:30:25,760 --> 00:30:28,070 being picked up through the skull. 701 00:30:28,070 --> 00:30:30,860 And you're picking up huge changes in hundreds of 702 00:30:30,860 --> 00:30:33,510 thousands of neurons, but you're able to do it 703 00:30:33,510 --> 00:30:35,950 millisecond by millisecond at the speed of thought. 704 00:30:39,410 --> 00:30:42,270 The same electrical signal for EEG and ERP, that evoke 705 00:30:42,270 --> 00:30:46,280 response potentials, with EEG you just watch it over time. 706 00:30:46,280 --> 00:30:49,210 So you can see these different rhythms that go with a person 707 00:30:49,210 --> 00:30:53,870 in coma, or in deep sleep, asleep, drowsy, relaxed. 708 00:30:53,870 --> 00:30:56,480 You can see these characteristic rhythms that 709 00:30:56,480 --> 00:30:58,190 people can measure. 710 00:30:58,190 --> 00:31:02,480 If you do an experiment, you can time lock these moment by 711 00:31:02,480 --> 00:31:06,140 moment to some stimulus or task you give the person. 712 00:31:06,140 --> 00:31:08,800 So here we're going to time lock these, and then you get a 713 00:31:08,800 --> 00:31:11,470 thing like this that says, here's a response, maybe the 714 00:31:11,470 --> 00:31:14,220 first moment after I see a word, a second moment after I 715 00:31:14,220 --> 00:31:16,050 see a word or something like that. 716 00:31:16,050 --> 00:31:18,430 So you can time lock large electrical 717 00:31:18,430 --> 00:31:20,890 responses in the brain. 718 00:31:20,890 --> 00:31:22,550 And you get some studies like this, and we'll come back to 719 00:31:22,550 --> 00:31:26,030 this, but here's a fun one in language for example. 720 00:31:26,030 --> 00:31:30,270 You read a sentence like, It was his first day at work, OK 721 00:31:30,270 --> 00:31:32,850 that's the baseline condition in purple, not a particularly 722 00:31:32,850 --> 00:31:34,195 exciting sentence. 723 00:31:34,195 --> 00:31:35,730 Although, your first day at work is actually pretty 724 00:31:35,730 --> 00:31:38,140 interesting-- but to read the sentence. 725 00:31:38,140 --> 00:31:41,090 How about this one: He spread the warm bread with socks. 726 00:31:41,090 --> 00:31:42,130 You go, Socks? 727 00:31:42,130 --> 00:31:44,280 I'm shocked, that makes no sense at all. 728 00:31:44,280 --> 00:31:47,350 What happens as you read it, here's in broken blue line, 729 00:31:47,350 --> 00:31:50,670 you go wow, and that's called the N400. 730 00:31:50,670 --> 00:31:53,730 But that's kind of cool, that's 400 milliseconds after 731 00:31:53,730 --> 00:31:56,100 you saw that word you said, I get it's socks but it doesn't 732 00:31:56,100 --> 00:31:56,960 make sense. 733 00:31:56,960 --> 00:32:01,180 So you're violating semantics. 734 00:32:01,180 --> 00:32:02,920 And then they have to do a control experiment. 735 00:32:02,920 --> 00:32:06,050 And a lot of psychology, in a course like this, we can't 736 00:32:06,050 --> 00:32:06,950 devote enough time to this. 737 00:32:06,950 --> 00:32:09,720 But I can tell you high quality research in psychology 738 00:32:09,720 --> 00:32:12,170 is high quality thoughtfulness like in any other field. 739 00:32:12,170 --> 00:32:15,580 You could say, well maybe it's not the word "socks" that's 740 00:32:15,580 --> 00:32:19,220 bothering you, maybe just because it's odd, just like a 741 00:32:19,220 --> 00:32:22,260 weirded out signal, it's a weirded out signal. 742 00:32:22,260 --> 00:32:25,070 So they do this, She put on her high-heeled shoes, but 743 00:32:25,070 --> 00:32:27,970 they put shoes in big print that you didn't expect. 744 00:32:27,970 --> 00:32:30,650 So now you're weirded out, but it makes sense. 745 00:32:30,650 --> 00:32:32,540 So what happens in your mind, you a very 746 00:32:32,540 --> 00:32:34,320 different response here. 747 00:32:34,320 --> 00:32:37,700 So here the meaning is wrong, here the size is wrong. 748 00:32:37,700 --> 00:32:39,950 And see you can read a person's mind in this sense, 749 00:32:39,950 --> 00:32:42,650 millisecond by millisecond as they understand something like 750 00:32:42,650 --> 00:32:44,420 a sentence. 751 00:32:44,420 --> 00:32:47,500 You can do it with babies, which is pretty cute, and 752 00:32:47,500 --> 00:32:49,410 incredibly exciting too. 753 00:32:49,410 --> 00:32:51,230 So we can measure to the milliseconds. 754 00:32:51,230 --> 00:32:53,420 Lots of people can take doing it, it's relatively 755 00:32:53,420 --> 00:32:54,720 inexpensive. 756 00:32:54,720 --> 00:32:56,550 Why don't we just run around and do that? 757 00:32:56,550 --> 00:32:59,060 And we do that at MIT, and lots of places do this too. 758 00:32:59,060 --> 00:33:02,000 Well, Spatial Resolution is really problematic, we don't 759 00:33:02,000 --> 00:33:04,230 know where in the brain the signals are 760 00:33:04,230 --> 00:33:05,070 really coming from. 761 00:33:05,070 --> 00:33:08,060 We know where the electrode is on the head, but that's 762 00:33:08,060 --> 00:33:10,330 picking up a lot of stuff below it, we don't know where 763 00:33:10,330 --> 00:33:12,010 the brain is coming from. 764 00:33:12,010 --> 00:33:14,050 The way I think about it a little bit, imagine you went 765 00:33:14,050 --> 00:33:16,000 to a football game, and you were on the outside of the 766 00:33:16,000 --> 00:33:18,410 stadium, and you heard big cheering on the side that you 767 00:33:18,410 --> 00:33:20,150 knew was MIT. 768 00:33:20,150 --> 00:33:22,270 You might think something good happened to MIT, then you hear 769 00:33:22,270 --> 00:33:25,340 big cheering on the side where CalTech team is sitting, and 770 00:33:25,340 --> 00:33:28,310 there's fans, it'd be the usual Rose Bowl. 771 00:33:32,010 --> 00:33:33,755 You might figure something good happened at CalTech, but 772 00:33:33,755 --> 00:33:35,510 you don't really know exactly what happened, and exactly 773 00:33:35,510 --> 00:33:37,380 where it happened. 774 00:33:37,380 --> 00:33:40,230 So we don't know where the signals are coming from in a 775 00:33:40,230 --> 00:33:42,560 very precise way. 776 00:33:42,560 --> 00:33:44,770 There's another method that's sort of very intriguing too, 777 00:33:44,770 --> 00:33:47,260 and we're just installing it at MIT, and you could be 778 00:33:47,260 --> 00:33:49,240 amongst the first generation of participants, if you so 779 00:33:49,240 --> 00:33:50,380 choose to be. 780 00:33:50,380 --> 00:33:53,330 This is called Magnetoencephalography, active 781 00:33:53,330 --> 00:33:55,230 neurons produce small magnetic fields. 782 00:33:55,230 --> 00:33:58,630 You can use a superconducting quantum device to measure this 783 00:33:58,630 --> 00:34:01,210 tiny, tiny change to the magnetic field, they're 784 00:34:01,210 --> 00:34:03,400 secondary to the neurons firing. 785 00:34:03,400 --> 00:34:06,390 These signals are problematic to measure because they're 786 00:34:06,390 --> 00:34:08,900 estimated to be 100 million times smaller than the earth's 787 00:34:08,900 --> 00:34:10,710 magnetic field. 788 00:34:10,710 --> 00:34:13,389 And all these measures we have in human brain function, all 789 00:34:13,389 --> 00:34:16,650 of them, the signal is terrible compared to the 790 00:34:16,650 --> 00:34:19,270 noise, it's terrible compared to the noise. 791 00:34:19,270 --> 00:34:21,710 And MEG might be the worst, there's a number of places 792 00:34:21,710 --> 00:34:25,750 that installed MEG, and had to take it out because the local 793 00:34:25,750 --> 00:34:29,270 traffic on the road was too big relative to the difference 794 00:34:29,270 --> 00:34:31,620 between the earth's magnetic field in the signal they get. 795 00:34:31,620 --> 00:34:34,920 Signal to noise is terrible in every noninvasive human brain 796 00:34:34,920 --> 00:34:36,250 measure we have. 797 00:34:36,250 --> 00:34:37,889 But you get something beautiful. 798 00:34:37,889 --> 00:34:42,230 Now, any mental thought we have of any interest of any 799 00:34:42,230 --> 00:34:45,370 kind, we pretty much understand to be the property 800 00:34:45,370 --> 00:34:48,150 not of a single part of the brain doing its thing, but a 801 00:34:48,150 --> 00:34:52,210 remarkable concert, different parts of your brain playing or 802 00:34:52,210 --> 00:34:53,750 interacting with one another. 803 00:34:53,750 --> 00:34:56,920 It's a symphony orchestra doing anything interesting in 804 00:34:56,920 --> 00:34:59,180 the human mind, and MEG can show that beautifully. 805 00:34:59,180 --> 00:35:01,770 So here's an individual's structural MRI that's been 806 00:35:01,770 --> 00:35:05,070 inflated, they've sort of blown it out like a balloon so 807 00:35:05,070 --> 00:35:06,400 it's sort of easy to look at. 808 00:35:06,400 --> 00:35:09,360 And what you're going to see now from Dale & Halgren in an 809 00:35:09,360 --> 00:35:13,520 MEG measurement millisecond by millisecond of what your brain 810 00:35:13,520 --> 00:35:17,550 does, roughly speaking, when you read a single word, OK 811 00:35:17,550 --> 00:35:18,800 here we go. 812 00:35:22,110 --> 00:35:24,490 See, back and forth, back and forth, and there's all this 813 00:35:24,490 --> 00:35:27,050 interaction feeding forward from when you see it, feeding 814 00:35:27,050 --> 00:35:29,040 being backward from parts of your brain that say, I think I 815 00:35:29,040 --> 00:35:31,970 know what it is, let's double check. 816 00:35:31,970 --> 00:35:33,040 Back and forth, back and forth. 817 00:35:33,040 --> 00:35:34,080 Let me do it one more time, because I think 818 00:35:34,080 --> 00:35:35,920 it's just so cool. 819 00:35:35,920 --> 00:35:39,580 Anything interesting that your brain does is an incredibly 820 00:35:39,580 --> 00:35:43,070 complicated millisecond by millisecond interaction 821 00:35:43,070 --> 00:35:45,810 between large scale brain networks. 822 00:35:45,810 --> 00:35:48,620 So here we go again, reading a single word, arrives in the 823 00:35:48,620 --> 00:35:50,340 back of the brain, front's thinking about back, front, 824 00:35:50,340 --> 00:35:52,210 back, front, back front. 825 00:35:52,210 --> 00:35:53,460 We read the word. 826 00:35:55,350 --> 00:35:59,280 It's just amazing, and MEG is one of the better measures for 827 00:35:59,280 --> 00:36:02,470 us to see this time based way in which your mind 828 00:36:02,470 --> 00:36:03,720 accomplishes things. 829 00:36:07,030 --> 00:36:09,070 The strengths are it has great temporal resolution, 830 00:36:09,070 --> 00:36:12,600 noninvasive, Spatial Resolution is it maybe better 831 00:36:12,600 --> 00:36:15,510 than EEG, or perhaps better, not as good as a fMRI, we'll 832 00:36:15,510 --> 00:36:17,470 come to that. 833 00:36:17,470 --> 00:36:20,200 And it only can measure neurons in the cortex that are 834 00:36:20,200 --> 00:36:22,900 parallel to the skull, so we can't see lots of things like 835 00:36:22,900 --> 00:36:24,385 support local structures like the hippocampus. 836 00:36:27,160 --> 00:36:29,410 So now we're moving to the measures that you most often 837 00:36:29,410 --> 00:36:32,080 see, but these other ones all help us a lot. 838 00:36:32,080 --> 00:36:34,280 And they are all derived from the following things. 839 00:36:34,280 --> 00:36:38,400 Sadly, for PET or fMRI, the most widely used studies to 840 00:36:38,400 --> 00:36:42,170 understand how your mind works, we can't interrogate 841 00:36:42,170 --> 00:36:44,650 the neurons to compute your mind, we can't, they're off 842 00:36:44,650 --> 00:36:46,050 bounds to us. 843 00:36:46,050 --> 00:36:48,810 The other measures you just saw are based on neurons. 844 00:36:48,810 --> 00:36:51,690 What we have to do is we have to look for gossipy neighbors, 845 00:36:51,690 --> 00:36:54,440 that is the vasculature that surrounds and supports the 846 00:36:54,440 --> 00:36:56,500 neurons that compute the mind. 847 00:36:56,500 --> 00:36:59,470 And we know the neurons require oxygen and glucose, 848 00:36:59,470 --> 00:37:02,860 metabolically to do their work, the cellular life. 849 00:37:02,860 --> 00:37:05,190 And the brain area's active, there's increased blood flow, 850 00:37:05,190 --> 00:37:06,900 and increased energy supplies that come to that. 851 00:37:06,900 --> 00:37:09,790 So it's all the sort of inference by the secondary 852 00:37:09,790 --> 00:37:13,270 consequence of neurons doing their business. 853 00:37:13,270 --> 00:37:16,310 So the brain is about 3 and 1/2 pounds, it's about 2% of 854 00:37:16,310 --> 00:37:18,310 your total body mass. 855 00:37:18,310 --> 00:37:22,980 So it has a tenfold, 20% extra demand of body oxygen, your 856 00:37:22,980 --> 00:37:25,880 brain cries out for oxygen at every moment. 857 00:37:25,880 --> 00:37:29,390 So 2% of your body, but 20% of the oxygen demand. 858 00:37:29,390 --> 00:37:32,060 And it's so sensitive that only 10 minutes of loss of 859 00:37:32,060 --> 00:37:35,260 oxygen can often cause irreversible brain damage, 860 00:37:35,260 --> 00:37:36,950 especially in structures like the hippocampus. 861 00:37:40,370 --> 00:37:46,030 The first discovery that blood changes that are going with 862 00:37:46,030 --> 00:37:48,150 brain changes, blood changes that are the sort of the 863 00:37:48,150 --> 00:37:52,240 echoes, if you will, a secondary consequence, is low 864 00:37:52,240 --> 00:37:54,360 tech character current machines. 865 00:37:54,360 --> 00:37:57,140 This is work from Angelo Mosso in the late 1880's, and he saw 866 00:37:57,140 --> 00:38:00,105 a patient who had a unusual sort of malformation, so he 867 00:38:00,105 --> 00:38:02,950 had almost no skull here. 868 00:38:02,950 --> 00:38:04,970 And he put on it something that measured the pressure 869 00:38:04,970 --> 00:38:09,760 there, and he also measured-- and what's shown here in red 870 00:38:09,760 --> 00:38:15,690 is this pressure as a control thing, that's pretty clever-- 871 00:38:15,690 --> 00:38:19,890 pulses of blood in the forearm, so those are in blue. 872 00:38:19,890 --> 00:38:22,850 That's the control, that's not just blood everywhere. 873 00:38:22,850 --> 00:38:24,770 And what he did is, the guy's still sitting there, nothing 874 00:38:24,770 --> 00:38:28,070 happening, and he noticed that when the church bells rang 875 00:38:28,070 --> 00:38:33,660 nearby, boom, this device picked up increased pressure 876 00:38:33,660 --> 00:38:34,960 over this part of the head. 877 00:38:34,960 --> 00:38:37,530 That's pretty cool, it has to be blood, it's not neurons, 878 00:38:37,530 --> 00:38:39,260 OK, it's blood. 879 00:38:39,260 --> 00:38:43,560 But now he has the signature of mental life in your brain, 880 00:38:43,560 --> 00:38:45,520 the blood consequence of a thought, which 881 00:38:45,520 --> 00:38:46,970 is I hear the Church. 882 00:38:46,970 --> 00:38:48,850 They asked the guy, does it have to be something that you 883 00:38:48,850 --> 00:38:50,740 hear, he says, did you make your prayers 884 00:38:50,740 --> 00:38:52,060 today, your Ave Maria? 885 00:38:52,060 --> 00:38:54,620 Again nothing happening peripherally, but boom, as he 886 00:38:54,620 --> 00:38:57,730 gives his answer, a change in blood pressure there. 887 00:38:57,730 --> 00:39:01,800 Or do math problem, boom, a change there. 888 00:39:01,800 --> 00:39:04,380 So all of the sudden, blood changes of a part of the brain 889 00:39:04,380 --> 00:39:08,120 become the witness to that part of the brain supporting 890 00:39:08,120 --> 00:39:11,110 the mental operations to do that task. 891 00:39:11,110 --> 00:39:13,513 And here's a PET study, the first weighted Positron 892 00:39:13,513 --> 00:39:16,400 Emission Tomography, which is basically used to measure 893 00:39:16,400 --> 00:39:20,280 local brain activity by looking at the consequences of 894 00:39:20,280 --> 00:39:23,590 photons disintegrating as they're measured in this sort 895 00:39:23,590 --> 00:39:25,090 of a device. 896 00:39:25,090 --> 00:39:27,860 And here's the way they use this task to discover which 897 00:39:27,860 --> 00:39:30,370 parts to map the neural organization 898 00:39:30,370 --> 00:39:32,040 of the human mind. 899 00:39:32,040 --> 00:39:35,140 So I need somebody who's willing to do a task at their 900 00:39:35,140 --> 00:39:38,460 seat, and it's just going to be reading words, or coming up 901 00:39:38,460 --> 00:39:39,560 with words. 902 00:39:39,560 --> 00:39:41,240 OK, thanks. 903 00:39:41,240 --> 00:39:42,330 Here you go, ready? 904 00:39:42,330 --> 00:39:45,560 Look at that, in our field we call that fixation, you're 905 00:39:45,560 --> 00:39:47,330 just looking, OK, just looking. 906 00:39:47,330 --> 00:39:48,720 Alright, good job. 907 00:39:48,720 --> 00:39:49,750 Ready for something else? 908 00:39:49,750 --> 00:39:52,830 Alright, now just look at these things, 909 00:39:52,830 --> 00:39:54,260 OK, you see the words? 910 00:39:54,260 --> 00:39:56,670 The technical word is reading. 911 00:39:56,670 --> 00:39:59,030 Alright, now imagine we did one more thing with you-- and 912 00:39:59,030 --> 00:40:00,130 actually if you were in a PET scanner 913 00:40:00,130 --> 00:40:00,940 here's what would happen. 914 00:40:00,940 --> 00:40:03,510 If in a PET scanner, you'd be sitting down there like that, 915 00:40:03,510 --> 00:40:06,070 there'd be a physician in their lab coat like this. 916 00:40:06,070 --> 00:40:09,460 There'd be physicist in the basement making up some sort 917 00:40:09,460 --> 00:40:13,110 of a tracer they're going to inject into you 918 00:40:13,110 --> 00:40:16,330 every round of this. 919 00:40:16,330 --> 00:40:18,470 Because that's what they need to sort of track this, and it 920 00:40:18,470 --> 00:40:20,690 comes up an elevator, and people take turns running down 921 00:40:20,690 --> 00:40:23,180 the hall with it, because it has a pretty short half-life. 922 00:40:23,180 --> 00:40:25,915 The shortness of its half-life is what makes you able to do 923 00:40:25,915 --> 00:40:27,300 these multiple measures. 924 00:40:27,300 --> 00:40:30,200 This is a pretty big deal process, and in fact the one 925 00:40:30,200 --> 00:40:32,935 or two PET sessions I ever attended, you would rotate who 926 00:40:32,935 --> 00:40:35,360 would run down the field with the radioactive substance, so 927 00:40:35,360 --> 00:40:38,490 you would share the radioactive substance. 928 00:40:41,840 --> 00:40:43,540 So now you've done that, and you feel like, I'm doing 929 00:40:43,540 --> 00:40:44,050 pretty good. 930 00:40:44,050 --> 00:40:44,940 So now they come and they say, are you 931 00:40:44,940 --> 00:40:45,960 ready for another injection? 932 00:40:45,960 --> 00:40:48,010 They have a catheter running into your arm, and they inject 933 00:40:48,010 --> 00:40:50,870 you again, here comes the radioactive stuff, the oxygen. 934 00:40:50,870 --> 00:40:54,440 And now they ask you to read the words aloud presented one 935 00:40:54,440 --> 00:40:56,330 at a time, why don't you just read aloud one 936 00:40:56,330 --> 00:40:57,411 at a time, go ahead. 937 00:40:57,411 --> 00:40:59,616 AUDIENCE: Rose, cat, apple, pen, plane. 938 00:40:59,616 --> 00:41:01,553 PROFESSOR: OK, and they say thank you very much, and we're 939 00:41:01,553 --> 00:41:03,510 going to do one more injection if that's OK with you, of 940 00:41:03,510 --> 00:41:05,430 radioactive substance. 941 00:41:05,430 --> 00:41:07,070 And now we're going to ask you to do one thing, and this is 942 00:41:07,070 --> 00:41:11,490 harder, as you see each word tell us a verb that describes 943 00:41:11,490 --> 00:41:13,710 what you might do with that object, or what a person might 944 00:41:13,710 --> 00:41:16,110 do, so go ahead, for rose tell us. 945 00:41:16,110 --> 00:41:19,519 AUDIENCE: Smell, pet, eat, write, fly. 946 00:41:19,519 --> 00:41:20,670 PROFESSOR: Perfect. 947 00:41:20,670 --> 00:41:22,490 Yeah, I can tell you that in the experiment they present a 948 00:41:22,490 --> 00:41:24,190 lot of these, and a lot of subjects after while just go 949 00:41:24,190 --> 00:41:29,800 use, use, use, use, hold, hold, hold, hold. 950 00:41:29,800 --> 00:41:31,050 But you did a good job, OK. 951 00:41:33,240 --> 00:41:35,040 This is just looking at something, this is looking at 952 00:41:35,040 --> 00:41:35,900 a word, which is reading. 953 00:41:35,900 --> 00:41:39,890 Now don't forget, we're the only species that ever read, 954 00:41:39,890 --> 00:41:43,050 reading has been around in our culture only for about 700 955 00:41:43,050 --> 00:41:46,840 years on any scale, and reading is an incredible thing 956 00:41:46,840 --> 00:41:47,710 to work correctly. 957 00:41:47,710 --> 00:41:50,990 And you saw the whole brain flicker to get it right. 958 00:41:50,990 --> 00:41:52,560 But now you're going to say the word in the next 959 00:41:52,560 --> 00:41:54,580 condition, so you're not just looking at the word, but 960 00:41:54,580 --> 00:41:56,030 you're also saying it. 961 00:41:56,030 --> 00:41:58,430 And now finally you're not only saying a word and looking 962 00:41:58,430 --> 00:42:00,270 at it, but you are thinking about it to come up with 963 00:42:00,270 --> 00:42:02,500 smell, or pet. 964 00:42:02,500 --> 00:42:04,150 So they say, what we're going to do is we're going to do a 965 00:42:04,150 --> 00:42:08,160 hierarchy of your mind, just looking, reading, reading and 966 00:42:08,160 --> 00:42:10,490 talking, reading and talking and thinking. 967 00:42:10,490 --> 00:42:12,500 And by comparing those different conditions, we'll 968 00:42:12,500 --> 00:42:15,050 subtract them against each other, and pull out the part 969 00:42:15,050 --> 00:42:19,090 of your mind that sees a word, that speaks a word, and that 970 00:42:19,090 --> 00:42:20,790 thinks about a word, and we'll separate 971 00:42:20,790 --> 00:42:23,700 those out in the brain. 972 00:42:23,700 --> 00:42:26,340 So basically the subtraction method. 973 00:42:26,340 --> 00:42:28,920 So when we compare looking at fixation versus looking at 974 00:42:28,920 --> 00:42:30,950 words, we'll see what part of your brain discovers that it's 975 00:42:30,950 --> 00:42:33,490 a word, knows how to read words, looking at words versus 976 00:42:33,490 --> 00:42:34,440 repeating them. 977 00:42:34,440 --> 00:42:38,490 We'll discover the basis of speech, speaking a word versus 978 00:42:38,490 --> 00:42:41,150 coming up with the verb, thinking about stuff, their 979 00:42:41,150 --> 00:42:42,970 meaning, and coming up with an answer. 980 00:42:46,640 --> 00:42:50,930 So again the idea is if you're saying something like pet for 981 00:42:50,930 --> 00:42:52,910 the cat, you're doing all these things. 982 00:42:52,910 --> 00:42:54,770 Or you might just be reading it aloud, and 983 00:42:54,770 --> 00:42:57,080 we'll subtract them. 984 00:42:57,080 --> 00:43:01,540 In both these conditions, here you saw a word and read it, 985 00:43:01,540 --> 00:43:06,010 here you saw a word and came up and produced a verb, you 986 00:43:06,010 --> 00:43:07,980 subtract these two and you end up with a 987 00:43:07,980 --> 00:43:09,320 statistical image like this. 988 00:43:09,320 --> 00:43:13,350 This is not a raw image of blood, all these you ever see 989 00:43:13,350 --> 00:43:16,200 those are statistics of the areas that differed by some 990 00:43:16,200 --> 00:43:18,540 statistical criterion between one condition and another. 991 00:43:18,540 --> 00:43:20,890 They're all statistics, they're not blood, or raw 992 00:43:20,890 --> 00:43:24,780 blood, that underlies it, but what you see is a statistic, 993 00:43:24,780 --> 00:43:26,110 and here's the statistic. 994 00:43:26,110 --> 00:43:28,740 Now in both of these cases, you saw the word. 995 00:43:28,740 --> 00:43:31,520 In this case you simply read it, in this case you read it 996 00:43:31,520 --> 00:43:34,110 in your head and you came up with a verb. 997 00:43:34,110 --> 00:43:36,710 But why don't we see anything back here? 998 00:43:36,710 --> 00:43:39,550 Why don't we see the seeing of the word, even though the 999 00:43:39,550 --> 00:43:40,960 seeing occurred in those conditions? 1000 00:43:40,960 --> 00:43:45,370 Why isn't it visible in this brain picture? 1001 00:43:45,370 --> 00:43:47,750 Because it's been subtracted out. 1002 00:43:47,750 --> 00:43:50,130 So always in these brain imaging experiments, for 1003 00:43:50,130 --> 00:43:52,570 reasons I'm about to tell you, we almost always have to do 1004 00:43:52,570 --> 00:43:53,600 some kind of subtraction. 1005 00:43:53,600 --> 00:43:57,590 And I'll tell you why, but that subtraction is very big. 1006 00:43:57,590 --> 00:44:00,040 Because what you subtract out, that's the heart of the 1007 00:44:00,040 --> 00:44:03,060 experiment, and your decision about what's a legitimate 1008 00:44:03,060 --> 00:44:03,850 subtraction. 1009 00:44:03,850 --> 00:44:06,610 And the reason we have to do it is this, look 1010 00:44:06,610 --> 00:44:07,330 at these two things. 1011 00:44:07,330 --> 00:44:09,190 Here's one condition, and here's the other condition. 1012 00:44:09,190 --> 00:44:11,950 Do you see that they look pretty similar? 1013 00:44:11,950 --> 00:44:14,450 Again, signal to noise. 1014 00:44:14,450 --> 00:44:18,700 Your brain is busy all the time, now we ask you to do 1015 00:44:18,700 --> 00:44:20,300 something and see the difference. 1016 00:44:20,300 --> 00:44:22,820 And the difference is very tiny by the way we measure it. 1017 00:44:22,820 --> 00:44:26,860 It's not tiny mentally, it's not tiny in terms of the 1018 00:44:26,860 --> 00:44:29,700 consequences for civilization in the world. 1019 00:44:29,700 --> 00:44:33,770 It's tiny because of the weird way we have to measure it. 1020 00:44:33,770 --> 00:44:36,760 I can tell you that if I've put on an optimal 1021 00:44:36,760 --> 00:44:38,600 checkerboard, the psychophysicists have said, 1022 00:44:38,600 --> 00:44:40,690 this turns on your visual cortex. 1023 00:44:40,690 --> 00:44:44,010 I'll get about a 3% to 5% change in your brain signal. 1024 00:44:44,010 --> 00:44:48,530 If you wave your arm, I can get 3% to 5% signal change in 1025 00:44:48,530 --> 00:44:49,870 your cortex here. 1026 00:44:49,870 --> 00:44:52,400 If I ask you to do everything in between seeing something 1027 00:44:52,400 --> 00:44:56,250 and moving your lips or hand, everything about thought, 1028 00:44:56,250 --> 00:45:00,690 emotion, memory, desire, motivation, everything that's 1029 00:45:00,690 --> 00:45:03,650 big in our life will get something like that one tenth 1030 00:45:03,650 --> 00:45:05,290 of 1% of the signal change. 1031 00:45:05,290 --> 00:45:08,395 One tenth of 1% of the signal change. 1032 00:45:08,395 --> 00:45:11,420 Yeah, Tyler's like yeah, that means you have to test a lot 1033 00:45:11,420 --> 00:45:14,660 of subjects, and work 40 years on your Ph.D. 1034 00:45:14,660 --> 00:45:17,280 So we have to do that subtraction, because if we 1035 00:45:17,280 --> 00:45:19,880 just take a picture of what's going on in your head, it's so 1036 00:45:19,880 --> 00:45:22,200 much that we can't tell what's going on at all. 1037 00:45:22,200 --> 00:45:23,980 And if we have you do something that's pretty big, 1038 00:45:23,980 --> 00:45:26,310 like seeing like a really provocative picture, we'll 1039 00:45:26,310 --> 00:45:29,220 just get one tenth of 1% of the signal change. 1040 00:45:29,220 --> 00:45:31,380 So we have to do the subtraction to have a hint. 1041 00:45:31,380 --> 00:45:33,540 And then we do one other weird thing, we don't have to but we 1042 00:45:33,540 --> 00:45:34,420 often do it. 1043 00:45:34,420 --> 00:45:36,630 We want to average people to make some general statement 1044 00:45:36,630 --> 00:45:40,060 about humanity, as far as we can do it, based on the 10 MIT 1045 00:45:40,060 --> 00:45:42,510 students we test. 1046 00:45:42,510 --> 00:45:45,030 So we scrunch everybody's brain into common space, 1047 00:45:45,030 --> 00:45:46,540 everybody's brain's a little bit different, like their 1048 00:45:46,540 --> 00:45:47,750 bodies are a little bit different. 1049 00:45:47,750 --> 00:45:50,320 We scrunch everybody to line them all up so we have a 1050 00:45:50,320 --> 00:45:51,820 common physical space. 1051 00:45:51,820 --> 00:45:54,250 So by the time you see this picture, it's a statistic on 1052 00:45:54,250 --> 00:45:57,000 an average of people in most cases, but you 1053 00:45:57,000 --> 00:45:58,020 get an amazing story. 1054 00:45:58,020 --> 00:46:00,810 Which up until these pictures-- 1055 00:46:00,810 --> 00:46:05,060 about the late 1980s, it was unimaginable that you could go 1056 00:46:05,060 --> 00:46:08,390 inside a living person's brain, and see what it is that 1057 00:46:08,390 --> 00:46:13,020 allows you to hear a word in auditory cortex, to see a word 1058 00:46:13,020 --> 00:46:18,910 in visual cortex, to move your mouth to speak, or to think, 1059 00:46:18,910 --> 00:46:21,820 what's the verb that goes with that word? 1060 00:46:21,820 --> 00:46:24,800 Unimaginable at your-- 1061 00:46:24,800 --> 00:46:26,900 OK, now I have to do the quick math, but you'll help me out-- 1062 00:46:26,900 --> 00:46:30,710 what year were you born in? 1063 00:46:30,710 --> 00:46:32,410 '82? 1064 00:46:32,410 --> 00:46:32,920 '92? 1065 00:46:32,920 --> 00:46:36,320 I know, at my age it all blends. '92? 1066 00:46:36,320 --> 00:46:38,580 OK, so just a year or two before you were born-- this 1067 00:46:38,580 --> 00:46:41,550 was 5 years before you were-- unimaginable that you could 1068 00:46:41,550 --> 00:46:42,750 see such a picture. 1069 00:46:42,750 --> 00:46:44,830 When I was a graduate student at Harvard, and the people at 1070 00:46:44,830 --> 00:46:46,370 Washington St. Louis University-- 1071 00:46:46,370 --> 00:46:47,600 who did the first of these-- 1072 00:46:47,600 --> 00:46:49,930 did an incredible service to the field. 1073 00:46:49,930 --> 00:46:51,880 Here we saw, oh my gosh, it was like landing on the moon. 1074 00:46:51,880 --> 00:46:54,320 Going inside the human brain, and knowing which part of the 1075 00:46:54,320 --> 00:46:57,500 brain endows us with human capacities. 1076 00:46:57,500 --> 00:47:00,600 Now, we can be appreciative or we can be skeptical 1077 00:47:00,600 --> 00:47:03,600 scientists, and we can say this, let's pick this one. 1078 00:47:03,600 --> 00:47:06,820 Let's compare seeing a word like "board," 1079 00:47:06,820 --> 00:47:07,970 versus seeing a fixation. 1080 00:47:07,970 --> 00:47:11,610 We do that subtraction, and that's seeing a word. 1081 00:47:11,610 --> 00:47:15,200 Just by common sense, what's wrong with this comparison? 1082 00:47:15,200 --> 00:47:18,460 It's OK it's not terrible. 1083 00:47:18,460 --> 00:47:20,419 How can you control it better? 1084 00:47:20,419 --> 00:47:25,180 To understand what this part of the brain is really doing? 1085 00:47:25,180 --> 00:47:28,426 I heard something? 1086 00:47:28,426 --> 00:47:31,000 Well partly it's a meaningful word, versus something that 1087 00:47:31,000 --> 00:47:33,390 doesn't mean anything to a plus. 1088 00:47:33,390 --> 00:47:35,460 But what else could you say is different between them? 1089 00:47:35,460 --> 00:47:36,362 Yeah? 1090 00:47:36,362 --> 00:47:37,346 [INAUDIBLE] 1091 00:47:37,346 --> 00:47:39,810 GUEST SPEAKER: [INAUDIBLE] 1092 00:47:39,810 --> 00:47:43,100 PROFESSOR: In this case, oh my gosh, yes, and I'll come back 1093 00:47:43,100 --> 00:47:44,960 to that, but let me not do that one for the moment, 1094 00:47:44,960 --> 00:47:47,690 because that's a giant story which I can't fit in today. 1095 00:47:47,690 --> 00:47:50,070 Yes your mind can be all over the place. 1096 00:47:50,070 --> 00:47:52,210 So that's definitely the case, so that's a good one. 1097 00:47:52,210 --> 00:47:52,700 Yeah? 1098 00:47:52,700 --> 00:47:54,972 GUEST SPEAKER: You could replace the plus, which is 1099 00:47:54,972 --> 00:47:57,090 like really small, with [INAUDIBLE] 1100 00:47:57,090 --> 00:47:58,882 PROFESSOR: Yeah, that's perfect, OK that's the way I 1101 00:47:58,882 --> 00:48:01,480 was going-- the other one's great too, two great comments. 1102 00:48:01,480 --> 00:48:03,140 Yeah you could say like, maybe this is a part of your brain 1103 00:48:03,140 --> 00:48:04,850 it goes with five things, or something this 1104 00:48:04,850 --> 00:48:05,920 big versus this big. 1105 00:48:05,920 --> 00:48:08,340 No you go, that's not so interesting, the part of your 1106 00:48:08,340 --> 00:48:10,360 brain that looks at something this big, versus this big. 1107 00:48:10,360 --> 00:48:13,150 But that's just as legitimate a conclusion here. 1108 00:48:13,150 --> 00:48:16,590 How about this, five different things, versus only this. 1109 00:48:16,590 --> 00:48:18,400 There's a lot of different ways in which you could say, 1110 00:48:18,400 --> 00:48:20,620 what is the mental operation that I've discovered in the 1111 00:48:20,620 --> 00:48:23,730 human brain and mind, it all comes down to the comparison. 1112 00:48:23,730 --> 00:48:26,880 So here's what they did to try to do a better job. 1113 00:48:26,880 --> 00:48:30,080 They showed you a more complicated thing that doesn't 1114 00:48:30,080 --> 00:48:32,000 mean anything. 1115 00:48:32,000 --> 00:48:36,490 A bunch of letters that you can't pronounce, a bunch of 1116 00:48:36,490 --> 00:48:38,330 letters that you can pronounce, but it's not a real 1117 00:48:38,330 --> 00:48:41,190 word, and here's the real world itself. 1118 00:48:41,190 --> 00:48:43,130 So if you want to say, what do you think this part of the 1119 00:48:43,130 --> 00:48:45,760 mind is doing? 1120 00:48:45,760 --> 00:48:48,160 What part the mind does this part of the brain allow to 1121 00:48:48,160 --> 00:48:50,870 happen in humans, and only humans on this planet? 1122 00:48:50,870 --> 00:48:54,150 And every word you ever read only happens because this part 1123 00:48:54,150 --> 00:48:55,880 of the brain does what it does. 1124 00:48:55,880 --> 00:48:57,360 What is that part of the brain doing? 1125 00:48:57,360 --> 00:48:59,090 Is it just simply responding too complicated 1126 00:48:59,090 --> 00:49:01,372 things, five of them? 1127 00:49:01,372 --> 00:49:04,260 No, not much, a little bit, but not much. 1128 00:49:04,260 --> 00:49:06,470 How about letters, letters are pretty interesting, but there 1129 00:49:06,470 --> 00:49:09,760 can't be a word by English, you can't pronounce this. 1130 00:49:09,760 --> 00:49:12,270 Not too interested? 1131 00:49:12,270 --> 00:49:14,930 A word, a set of letters you've never seen together 1132 00:49:14,930 --> 00:49:17,290 before, but you can pronounce by the rules of English. 1133 00:49:17,290 --> 00:49:18,710 Boom. 1134 00:49:18,710 --> 00:49:20,870 That's what I do, says this part of the brain, 1135 00:49:20,870 --> 00:49:22,360 that's what I do. 1136 00:49:22,360 --> 00:49:25,080 I say, I see something, and it's possibly a word and I can 1137 00:49:25,080 --> 00:49:26,780 say it by the rules of English. 1138 00:49:26,780 --> 00:49:27,900 And by the way, if it's a word I've done 1139 00:49:27,900 --> 00:49:29,430 before, I do that too. 1140 00:49:29,430 --> 00:49:31,600 I'm pretty flexible, I can do new words, I can do words I've 1141 00:49:31,600 --> 00:49:33,030 known before. 1142 00:49:33,030 --> 00:49:39,180 It matches what you see with language, that's reading. 1143 00:49:39,180 --> 00:49:41,870 Only our species can take our visual system, and the 1144 00:49:41,870 --> 00:49:44,730 language you learn as a child, and put them together, and 1145 00:49:44,730 --> 00:49:47,180 allow our civilization to read. 1146 00:49:47,180 --> 00:49:52,400 And this is a part of the brain where those roads meet. 1147 00:49:52,400 --> 00:49:54,570 And by the way, we talked about local and global, the 1148 00:49:54,570 --> 00:49:56,470 forest and the trees. 1149 00:49:56,470 --> 00:49:58,416 And consistent with what we talked about the split brain 1150 00:49:58,416 --> 00:50:00,932 patients, looking at global stuff right hemisphere, if 1151 00:50:00,932 --> 00:50:02,640 you're looking at local stuff, left hemisphere. 1152 00:50:02,640 --> 00:50:05,270 So we like it when the information we have from 1153 00:50:05,270 --> 00:50:07,170 split-brain patients, or stroke patients aligns with 1154 00:50:07,170 --> 00:50:10,210 healthy people doing a task as they typically do. 1155 00:50:10,210 --> 00:50:11,600 Because then we sort of believe there's something 1156 00:50:11,600 --> 00:50:13,590 right about that. 1157 00:50:13,590 --> 00:50:18,610 So PET, pretty good spatial resolution, I mean, depends 1158 00:50:18,610 --> 00:50:19,750 what you mean by good. 1159 00:50:19,750 --> 00:50:22,860 My neuroscience colleagues dismiss everything we ever do 1160 00:50:22,860 --> 00:50:25,310 as sort of pathetically imprecise. 1161 00:50:25,310 --> 00:50:27,380 But 5 to 10 millimeters, not as good as fMRI. 1162 00:50:29,950 --> 00:50:32,160 The temporal resolution is very poor we can only take one 1163 00:50:32,160 --> 00:50:35,560 picture that lasts about a minute, and averages 1164 00:50:35,560 --> 00:50:36,770 everything across that. 1165 00:50:36,770 --> 00:50:40,280 You have to inject people with radioactive stuff, and it's 1166 00:50:40,280 --> 00:50:42,120 correlational. 1167 00:50:42,120 --> 00:50:43,880 But it has one other thing that's really, really 1168 00:50:43,880 --> 00:50:46,020 interesting, Positron Emission Tomography. 1169 00:50:46,020 --> 00:50:49,240 Because you're injecting a radioactive label, you can 1170 00:50:49,240 --> 00:50:51,510 create different kinds of labels that go to different 1171 00:50:51,510 --> 00:50:52,620 parts of the brain. 1172 00:50:52,620 --> 00:50:55,830 So here's Parkinson's disease, which involves damage the 1173 00:50:55,830 --> 00:50:57,840 Substantia nigra, and the Basal Ganglia. 1174 00:50:57,840 --> 00:51:00,770 Here's a healthy persons Substantia nigra, and here's a 1175 00:51:00,770 --> 00:51:02,640 person with Parkinson's disease, where these cells 1176 00:51:02,640 --> 00:51:04,210 have died away. 1177 00:51:04,210 --> 00:51:06,760 Typically, at least 80% of these have to die before a 1178 00:51:06,760 --> 00:51:11,410 person shows Parkinson's disease symptoms clinically. 1179 00:51:11,410 --> 00:51:14,200 Here's an injection of radioactive stuff using PET 1180 00:51:14,200 --> 00:51:17,840 that binds to Dopamine receiving neurons. 1181 00:51:17,840 --> 00:51:20,210 And you can see that in the living Parkinson's patient, 1182 00:51:20,210 --> 00:51:22,710 this tremendous reduction in these 1183 00:51:22,710 --> 00:51:24,960 receptors waiting for Dopamine. 1184 00:51:24,960 --> 00:51:26,040 In a living patient 1185 00:51:26,040 --> 00:51:28,410 specifically Dopamine receptors. 1186 00:51:28,410 --> 00:51:30,860 So that's a disease. 1187 00:51:30,860 --> 00:51:33,550 Here's why video games are taking over the world. 1188 00:51:33,550 --> 00:51:34,160 Oh no, not yet. 1189 00:51:34,160 --> 00:51:35,530 We can do one more thing. 1190 00:51:35,530 --> 00:51:38,550 We can track the disease from a typical person, to a person 1191 00:51:38,550 --> 00:51:41,680 with moderate Parkinson's disease or severe. 1192 00:51:41,680 --> 00:51:43,850 Within the disease, we can see differences. 1193 00:51:43,850 --> 00:51:46,860 But here's why video games are taking over the world, because 1194 00:51:46,860 --> 00:51:49,670 if we take a healthy person, young adults, give them this 1195 00:51:49,670 --> 00:51:53,640 kind of Dopamine binding tracer, and have them play a 1196 00:51:53,640 --> 00:51:55,680 video game, two things happen. 1197 00:51:55,680 --> 00:51:59,150 A, the parts of your brain that are involved in reward, 1198 00:51:59,150 --> 00:52:01,020 Dopamine, is the strongest to reward 1199 00:52:01,020 --> 00:52:02,100 neurotransmitter that we know. 1200 00:52:02,100 --> 00:52:07,430 Things go crazy, and what this graph is showing you is the 1201 00:52:07,430 --> 00:52:10,260 better you do, the more rewarded you are. 1202 00:52:10,260 --> 00:52:12,900 This is why you will go for the next level, because to get 1203 00:52:12,900 --> 00:52:14,720 that dopamine fix, you got to keep going. 1204 00:52:18,130 --> 00:52:20,210 And we think these reward mechanisms underlie 1205 00:52:20,210 --> 00:52:23,330 everything, in many ways they relate to everything. 1206 00:52:23,330 --> 00:52:26,890 Why do you do whatever you do, because at some level, in some 1207 00:52:26,890 --> 00:52:28,910 way, you find it rewarding. 1208 00:52:28,910 --> 00:52:33,070 And the data is very compelling that way. 1209 00:52:33,070 --> 00:52:36,570 The last method I'll talk about is functional MRI, and 1210 00:52:36,570 --> 00:52:39,310 it's the one that's most widely visible. 1211 00:52:39,310 --> 00:52:42,256 So you sit in a scanner, stimula are presented to you 1212 00:52:42,256 --> 00:52:43,360 to perform a task. 1213 00:52:43,360 --> 00:52:45,700 We do a lot of stuff in our lab with children, we show 1214 00:52:45,700 --> 00:52:48,640 them how the frog would do it. 1215 00:52:48,640 --> 00:52:50,680 For those of you who've done a functional MRI experiment, 1216 00:52:50,680 --> 00:52:52,280 because there were so many hands that were put up. 1217 00:52:52,280 --> 00:52:55,570 Do any of you want to say a word about your experience 1218 00:52:55,570 --> 00:52:56,850 doing that? 1219 00:52:56,850 --> 00:52:59,280 What was it like, easy, huge fun, recommend, 1220 00:52:59,280 --> 00:53:00,200 no, not so much fun. 1221 00:53:00,200 --> 00:53:03,720 It will vary a little bit. 1222 00:53:03,720 --> 00:53:04,970 We said noisy. 1223 00:53:09,630 --> 00:53:12,174 Some people find it claustrophobic. 1224 00:53:12,174 --> 00:53:13,108 GUEST SPEAKER: I dont know, I didn't really do anything. 1225 00:53:13,108 --> 00:53:16,380 I just had to sit there for a really long time and not move. 1226 00:53:16,380 --> 00:53:18,030 PROFESSOR: Oh, so they didn't ask you to do a task, maybe. 1227 00:53:18,030 --> 00:53:20,716 GUEST SPEAKER: Well, for a big part of it, I 1228 00:53:20,716 --> 00:53:21,890 was watching a movie. 1229 00:53:21,890 --> 00:53:25,840 PROFESSOR: So for the student they were watching a movie not 1230 00:53:25,840 --> 00:53:27,242 doing anything, 1231 00:53:27,242 --> 00:53:29,990 GUEST SPEAKER: [INAUDIBLE] 1232 00:53:29,990 --> 00:53:31,640 PROFESSOR: You were doing yes or no clicks. 1233 00:53:31,640 --> 00:53:33,380 So that would be typical functional MRI kind of 1234 00:53:33,380 --> 00:53:36,110 experiment, some of them are more obnoxious, some are less, 1235 00:53:36,110 --> 00:53:40,000 some are funny, some are not as funny. 1236 00:53:40,000 --> 00:53:42,340 Any other experiences? 1237 00:53:42,340 --> 00:53:46,830 Was it comfortable, not so comfortable, medium. 1238 00:53:46,830 --> 00:53:49,755 Anybody else want to share? 1239 00:53:49,755 --> 00:53:50,530 No, OK. 1240 00:53:50,530 --> 00:53:51,780 OK. 1241 00:53:54,320 --> 00:53:56,940 So how does this work? 1242 00:53:56,940 --> 00:54:00,370 Functional MRI takes advantage of MRI but it focuses on 1243 00:54:00,370 --> 00:54:03,260 hemoglobin, the stuff that carries oxygen in your blood. 1244 00:54:03,260 --> 00:54:06,920 And it rests on the fact that after oxygen has been 1245 00:54:06,920 --> 00:54:10,060 extracted it's more sensitive to the magnetic field than 1246 00:54:10,060 --> 00:54:11,470 oxygenated hemoglobin. 1247 00:54:11,470 --> 00:54:12,960 So it's like this. 1248 00:54:12,960 --> 00:54:19,160 Here's basically capillaries and veins, arteries and veins. 1249 00:54:19,160 --> 00:54:22,050 And as you go through the capillary bed, the smallest 1250 00:54:22,050 --> 00:54:25,400 vessels, neurons are extracting oxygen to support 1251 00:54:25,400 --> 00:54:27,700 their physical life. 1252 00:54:27,700 --> 00:54:31,260 What happens when this part of the brain gets active, is that 1253 00:54:31,260 --> 00:54:35,070 more oxygen is extracted to support the active neurons. 1254 00:54:35,070 --> 00:54:40,140 So we call this BOLD effect, blood oxygen level dependent. 1255 00:54:40,140 --> 00:54:43,560 So we're measuring the change in blood, changes the ratio of 1256 00:54:43,560 --> 00:54:46,420 oxygenated to deoxygenated hemoglobins, that changes the 1257 00:54:46,420 --> 00:54:48,430 magnetic field as we measure it. 1258 00:54:48,430 --> 00:54:51,100 And that's what we directly measure, not the neurons. 1259 00:54:51,100 --> 00:54:53,770 So if the neurons are using up oxygen, why does the BOLD 1260 00:54:53,770 --> 00:54:57,570 signal increase, why does this ratio go up? 1261 00:54:57,570 --> 00:55:00,480 Because intuitively you'd think it would go down, 1262 00:55:00,480 --> 00:55:02,940 because oxygen is being extracted at a higher rate. 1263 00:55:06,260 --> 00:55:09,140 If you look at oxygen being extracted, right after 1264 00:55:09,140 --> 00:55:13,440 something happens, 10 seconds, there's an 1265 00:55:13,440 --> 00:55:14,730 initial dip of oxygen. 1266 00:55:14,730 --> 00:55:17,830 That's the neurons extracting oxygen to replenish themselves 1267 00:55:17,830 --> 00:55:20,750 from their activity, their activity has been to give your 1268 00:55:20,750 --> 00:55:23,490 mind its life. 1269 00:55:23,490 --> 00:55:27,950 Then what happens is there's this vast oversupply for much 1270 00:55:27,950 --> 00:55:30,180 longer time. 1271 00:55:30,180 --> 00:55:33,420 Intuitively, it's as if we said it's so important to 1272 00:55:33,420 --> 00:55:35,730 metabolically support the neurons that make up our 1273 00:55:35,730 --> 00:55:39,580 minds, that if some areas demanding a lot of blood, we 1274 00:55:39,580 --> 00:55:43,990 send over way too much extra as soon as we can, from a 1275 00:55:43,990 --> 00:55:47,480 distance to make sure everything's OK. 1276 00:55:47,480 --> 00:55:51,720 And because our measurement is so sad, we almost can never 1277 00:55:51,720 --> 00:55:54,720 measure this initial dip. 1278 00:55:54,720 --> 00:55:58,470 We almost always measure the sustained oversupply of oxygen 1279 00:55:58,470 --> 00:56:00,470 to that part of the brain. 1280 00:56:00,470 --> 00:56:04,040 So you could say it's such a house of cards. 1281 00:56:04,040 --> 00:56:07,690 The oversupply of the blood going to a part of the brain 1282 00:56:07,690 --> 00:56:10,840 changes the balance of oxygenated to deoxygenated 1283 00:56:10,840 --> 00:56:13,950 hemoglobin that changes the magnetic property. 1284 00:56:13,950 --> 00:56:16,440 And that's how we try to figure out what that part of 1285 00:56:16,440 --> 00:56:18,950 the brain is doing for your mind. 1286 00:56:18,950 --> 00:56:22,000 But it works pretty well in some cases. 1287 00:56:22,000 --> 00:56:26,820 Decent Spatial Resolution, no injection, you can zoom in a 1288 00:56:26,820 --> 00:56:28,710 scanner and do a lot of different things. 1289 00:56:28,710 --> 00:56:31,500 Modest Temporal Resolution, because it's not milliseconds, 1290 00:56:31,500 --> 00:56:34,960 it's always on the order of seconds, that's correlational, 1291 00:56:34,960 --> 00:56:36,560 not causal. 1292 00:56:36,560 --> 00:56:38,150 But you get some amazing results, I'm just going to 1293 00:56:38,150 --> 00:56:40,300 present to you two or three. 1294 00:56:40,300 --> 00:56:42,800 So here's one, a thing we're very interested about humans 1295 00:56:42,800 --> 00:56:44,420 is empathy. 1296 00:56:44,420 --> 00:56:48,500 How much we understand and feel other people's happiness, 1297 00:56:48,500 --> 00:56:50,200 or sadness, or pain. 1298 00:56:50,200 --> 00:56:52,430 So the "observation or imagination of another person 1299 00:56:52,430 --> 00:56:55,420 in a particular emotional state automatically activates 1300 00:56:55,420 --> 00:56:58,660 a representation of that state in the observer," empathy. 1301 00:56:58,660 --> 00:57:02,780 And how do we understand how another person feels, and we 1302 00:57:02,780 --> 00:57:04,570 think that's a big thing in how we relate to 1303 00:57:04,570 --> 00:57:06,680 one another as humans. 1304 00:57:06,680 --> 00:57:11,250 So Tania Singer did the following experiment, we 1305 00:57:11,250 --> 00:57:12,280 talked about this before a little 1306 00:57:12,280 --> 00:57:13,960 bit, embodied cognition. 1307 00:57:13,960 --> 00:57:17,420 That we understand others out there by the feelings 1308 00:57:17,420 --> 00:57:18,590 we know within us. 1309 00:57:18,590 --> 00:57:20,620 We don't know their feelings, but we know our 1310 00:57:20,620 --> 00:57:22,470 feelings inside us. 1311 00:57:22,470 --> 00:57:25,390 So here's what she did, she brought in pairs of people who 1312 00:57:25,390 --> 00:57:28,920 were friends, or romantic partners. 1313 00:57:28,920 --> 00:57:33,650 And she either had them get some pain, it was a shock, 1314 00:57:33,650 --> 00:57:38,090 within ethical boundaries, but not pleasant, that's the pain. 1315 00:57:38,090 --> 00:57:41,780 Or, you got to watch through a video camera, while you're 1316 00:57:41,780 --> 00:57:44,730 being imaged, your partner getting the shock. 1317 00:57:44,730 --> 00:57:47,370 So think about somebody you care about and think about 1318 00:57:47,370 --> 00:57:49,960 them getting something painful, and how you would 1319 00:57:49,960 --> 00:57:51,490 feel at that moment. 1320 00:57:51,490 --> 00:57:54,330 And they asked in the brain, what's similar and dissimilar, 1321 00:57:54,330 --> 00:57:56,940 and we'll focus on what's similar right now, between 1322 00:57:56,940 --> 00:58:01,250 feeling pain yourself, and observing pain in somebody you 1323 00:58:01,250 --> 00:58:05,140 care about, emphasizing with the pain you see them having. 1324 00:58:05,140 --> 00:58:07,900 And what they found is two areas, something of an 1325 00:58:07,900 --> 00:58:10,270 Anterior Cingulate, and something in the Insula, which 1326 00:58:10,270 --> 00:58:13,500 we talked about before, where there was a lot of overlap. 1327 00:58:13,500 --> 00:58:17,110 So this phrase, I'm feeling your pain, in your brain when 1328 00:58:17,110 --> 00:58:20,800 you feel for somebody else's pain in this physical sense, 1329 00:58:20,800 --> 00:58:23,910 you turn on some of the same brain areas as when you feel 1330 00:58:23,910 --> 00:58:25,660 physical pain directly. 1331 00:58:25,660 --> 00:58:27,690 It's as if the basis to imagine another person's 1332 00:58:27,690 --> 00:58:31,290 feelings is the feelings you know so well yourself. 1333 00:58:31,290 --> 00:58:33,600 And this is literally shown now by the brain imaging. 1334 00:58:33,600 --> 00:58:36,430 It could've been a story, a metaphor, an argument, this is 1335 00:58:36,430 --> 00:58:40,350 scientific evidence that supports that likelihood. 1336 00:58:40,350 --> 00:58:43,970 So we're going to expend it in a slightly fun way. 1337 00:58:43,970 --> 00:58:46,970 There's been a lot of study in neuroeconomics thinking about 1338 00:58:46,970 --> 00:58:50,120 how we think about, for example, things like trust. 1339 00:58:50,120 --> 00:58:52,210 So one game, and there's a number of them, is called the 1340 00:58:52,210 --> 00:58:53,000 ultimatum game. 1341 00:58:53,000 --> 00:58:54,260 And many people probably know this, but let me 1342 00:58:54,260 --> 00:58:55,520 remind you of this. 1343 00:58:55,520 --> 00:58:57,900 This version of it has two players, a 1344 00:58:57,900 --> 00:59:00,520 proposer, and a responder. 1345 00:59:00,520 --> 00:59:03,210 And what they do is they give to proposer a certain amount 1346 00:59:03,210 --> 00:59:11,450 of money, and the proposer is allowed to make an offer to 1347 00:59:11,450 --> 00:59:13,500 the responder. 1348 00:59:13,500 --> 00:59:17,990 If the responder says, No, nobody gets any money. 1349 00:59:17,990 --> 00:59:20,620 Usually people offered about 50%, so let's make this 1350 00:59:20,620 --> 00:59:22,050 concrete just for a moment. 1351 00:59:22,050 --> 00:59:24,620 Can I pick you for a second? 1352 00:59:24,620 --> 00:59:25,870 You can decline. 1353 00:59:28,320 --> 00:59:34,080 Imagine if Tyler came over to me and give me $10, and I 1354 00:59:34,080 --> 00:59:37,710 said, how would you feel if I gave you five and I kept five. 1355 00:59:37,710 --> 00:59:39,400 What do you think? 1356 00:59:39,400 --> 00:59:40,240 Might you go for It? 1357 00:59:40,240 --> 00:59:42,010 GUEST SPEAKER: Yeah, sure. 1358 00:59:42,010 --> 00:59:43,620 PROFESSOR: I mean, you go, I'm $5 dollars ahead, you're $5 1359 00:59:43,620 --> 00:59:47,440 ahead, Tyler won't eat this month because graduate student 1360 00:59:47,440 --> 00:59:50,480 stipends are modest, but it's a zero sum game in the end. 1361 00:59:53,440 --> 00:59:57,270 So now Tyler comes over hands me 10 more dollars, and I 1362 00:59:57,270 --> 00:59:59,300 offer you one. 1363 00:59:59,300 --> 01:00:01,950 What's your first feeling assuming that I wasn't your 1364 01:00:01,950 --> 01:00:03,200 teacher grading you? 1365 01:00:06,230 --> 01:00:08,660 He saw me get ten, I say here's one. 1366 01:00:08,660 --> 01:00:09,972 What's your feeling? 1367 01:00:09,972 --> 01:00:11,780 Think about it just for-- 1368 01:00:11,780 --> 01:00:13,136 GUEST SPEAKER: You'd feel kind of cheated. 1369 01:00:13,136 --> 01:00:14,040 PROFESSOR: --yeah. 1370 01:00:14,040 --> 01:00:18,490 You don't have to, by purely economic perspective, would 1371 01:00:18,490 --> 01:00:20,690 you be ahead by taking that dollar? 1372 01:00:20,690 --> 01:00:21,530 Yeah. 1373 01:00:21,530 --> 01:00:24,140 A dollar's a dollar, $2 is $2, but people 1374 01:00:24,140 --> 01:00:26,430 have a sense of fairness. 1375 01:00:26,430 --> 01:00:32,410 Even to their own detriment, if you offer $2 and lower. 1376 01:00:32,410 --> 01:00:35,990 Even knowing that you're just ruining $1 or two you would've 1377 01:00:35,990 --> 01:00:38,630 gotten for nothing, except saying yes, people half the 1378 01:00:38,630 --> 01:00:40,500 time will say no. 1379 01:00:40,500 --> 01:00:42,540 It's like, you are so unfair-- 1380 01:00:42,540 --> 01:00:45,210 you were saying to me, I would never say this to you-- you 1381 01:00:45,210 --> 01:00:47,960 are so unfair, that we're going to take us both down, 1382 01:00:47,960 --> 01:00:49,750 rather than you have the pleasure of the $8. 1383 01:00:49,750 --> 01:00:51,620 OK It's so unfair, that my sense 1384 01:00:51,620 --> 01:00:54,860 of fairness is disturbed. 1385 01:00:54,860 --> 01:00:57,010 It's an interesting way to think about it, imagine a 1386 01:00:57,010 --> 01:01:00,215 friend of yours is handed $10, and they offer you half, and 1387 01:01:00,215 --> 01:01:02,810 if you say no, nobody gets anything, so 1388 01:01:02,810 --> 01:01:05,210 it's a trust game. 1389 01:01:05,210 --> 01:01:07,310 They had the people in the scanner playing this game with 1390 01:01:07,310 --> 01:01:09,490 two people they saw on a video monitor. 1391 01:01:09,490 --> 01:01:11,930 The two people they're playing with are set up. 1392 01:01:11,930 --> 01:01:13,690 The person in the scanner is the real participant, the 1393 01:01:13,690 --> 01:01:16,490 people out there they see, are confederates, 1394 01:01:16,490 --> 01:01:17,700 they're play actors. 1395 01:01:17,700 --> 01:01:20,890 And one is a fair person, here's $5, thank you, here's 1396 01:01:20,890 --> 01:01:22,430 $5, thank you. 1397 01:01:22,430 --> 01:01:26,160 Here's $6, oh, you're awesome, we can get along, And then 1398 01:01:26,160 --> 01:01:28,450 there's an unfair player, here's $1. 1399 01:01:28,450 --> 01:01:31,300 And you go, why is this guy a jerk? 1400 01:01:31,300 --> 01:01:33,210 How about $2? 1401 01:01:33,210 --> 01:01:36,670 And after a while, you go the fair player was very decent, 1402 01:01:36,670 --> 01:01:38,070 this unfair player-- 1403 01:01:38,070 --> 01:01:40,450 who you believe is part of the experiment, but is a set up-- 1404 01:01:40,450 --> 01:01:42,310 and you're just thinking, why is this person such a jerk? 1405 01:01:42,310 --> 01:01:45,300 They're constantly getting $10, and constantly giving me 1406 01:01:45,300 --> 01:01:46,380 one or two. 1407 01:01:46,380 --> 01:01:47,630 No, no, no thank you. 1408 01:01:51,840 --> 01:01:55,870 Now, you get a shock, and you see these two strangers, one 1409 01:01:55,870 --> 01:01:58,210 of whom was a wonderful, fair player, and one of whom was an 1410 01:01:58,210 --> 01:01:59,780 absurdly unfair player. 1411 01:01:59,780 --> 01:02:02,350 You see them get a shock. 1412 01:02:02,350 --> 01:02:04,300 And they had both men and women in the scanner watching 1413 01:02:04,300 --> 01:02:05,220 these things happen. 1414 01:02:05,220 --> 01:02:07,450 And here's what happened, and it's kind of 1415 01:02:07,450 --> 01:02:09,280 funny, but you know. 1416 01:02:09,280 --> 01:02:12,830 For the women they had overlap again between the parts of the 1417 01:02:12,830 --> 01:02:15,710 brain to turn on in here in the insula, when they got a 1418 01:02:15,710 --> 01:02:19,240 shock, and when either the fair player got a shock, or 1419 01:02:19,240 --> 01:02:20,350 the unfair player. 1420 01:02:20,350 --> 01:02:23,150 They felt bad for both by this measure. 1421 01:02:23,150 --> 01:02:25,840 Look at the men in the study. 1422 01:02:25,840 --> 01:02:29,730 I feel bad if the fair guy gets it, but this part of the 1423 01:02:29,730 --> 01:02:31,950 brain's like, yeah, give it to 'em, can 1424 01:02:31,950 --> 01:02:35,370 you push up the voltage? 1425 01:02:35,370 --> 01:02:37,590 It just came out this way, whether it would work that way 1426 01:02:37,590 --> 01:02:40,930 under all circumstances, all ages, all societies, other 1427 01:02:40,930 --> 01:02:42,250 groups of men and women, don't know. 1428 01:02:42,250 --> 01:02:45,610 But in this sample in the United Kingdom, 1429 01:02:45,610 --> 01:02:49,050 the men had no empathy. 1430 01:02:49,050 --> 01:02:51,480 It's worse than that, it's worse than they had no 1431 01:02:51,480 --> 01:02:54,520 empathy, let me show you this. 1432 01:02:54,520 --> 01:02:56,940 If they asked to indicate their 1433 01:02:56,940 --> 01:02:59,020 desire for revenge against-- 1434 01:02:59,020 --> 01:03:00,390 this is a behavioral response-- their desire for 1435 01:03:00,390 --> 01:03:03,370 revenge against the bad player. 1436 01:03:03,370 --> 01:03:06,390 I don't think they pursued the unfair player down the street, 1437 01:03:06,390 --> 01:03:07,760 but just that feeling. 1438 01:03:07,760 --> 01:03:11,550 And the women said, a little bit, the men said yes, if only 1439 01:03:11,550 --> 01:03:13,550 I could take down this person, that would be great. 1440 01:03:13,550 --> 01:03:15,160 And here's the amazing thing, we'll come back to the 1441 01:03:15,160 --> 01:03:16,520 structure called a nucleus accumbens. 1442 01:03:16,520 --> 01:03:19,450 It sits in the bottom of the Basal Ganglia. 1443 01:03:19,450 --> 01:03:22,590 It's the structure that in the human brain is most identified 1444 01:03:22,590 --> 01:03:25,675 with reward and pleasure, most identified with reward and 1445 01:03:25,675 --> 01:03:27,540 pleasure by fMRI imaging. 1446 01:03:27,540 --> 01:03:29,280 Look at the nucleus accumbens when the 1447 01:03:29,280 --> 01:03:33,930 unfair player gets zapped. 1448 01:03:33,930 --> 01:03:37,770 The women, nothing much, the men boom, big reward. 1449 01:03:37,770 --> 01:03:40,380 Revenge is rewarding in their brain. 1450 01:03:40,380 --> 01:03:44,260 No sympathy, and lots of revenge satisfaction for the 1451 01:03:44,260 --> 01:03:45,260 unfair player. 1452 01:03:45,260 --> 01:03:47,870 Now you can decide on your own life who this applies to or 1453 01:03:47,870 --> 01:03:50,880 not, but it's sort of fun to explore 1454 01:03:50,880 --> 01:03:51,680 these different things. 1455 01:03:51,680 --> 01:03:55,140 How we form ideas about empathy, trust, whether they 1456 01:03:55,140 --> 01:03:57,490 are in a society we grow up in. 1457 01:03:57,490 --> 01:04:00,120 Somewhat different on average men and women, huge ranges 1458 01:04:00,120 --> 01:04:01,840 within men huge ranges within women. 1459 01:04:01,840 --> 01:04:03,530 So it's a sort of fun thing to explore. 1460 01:04:03,530 --> 01:04:07,540 Let me end with something that's much more difficult and 1461 01:04:07,540 --> 01:04:10,050 disturbing, but another place where imaging is giving us 1462 01:04:10,050 --> 01:04:14,260 insights that you could not imagined having some time ago. 1463 01:04:14,260 --> 01:04:16,760 So this is a very difficult case, I don't know if any of 1464 01:04:16,760 --> 01:04:19,370 you gone through it, I don't wish it for you. 1465 01:04:19,370 --> 01:04:21,220 Some of you probably have, and many of you will at sometime 1466 01:04:21,220 --> 01:04:23,930 in your life, when you have to make an end of life decision. 1467 01:04:23,930 --> 01:04:30,380 And amongst the most famous of these cases was Terry Schiavo. 1468 01:04:30,380 --> 01:04:32,990 Now I don't know that name even rings a bell for you, but 1469 01:04:32,990 --> 01:04:36,670 it got very, very famous amongst these kinds of cases. 1470 01:04:36,670 --> 01:04:39,260 So she had a cardiac arrest, she had took a lot of diet 1471 01:04:39,260 --> 01:04:40,700 pills, and that may have contributed. 1472 01:04:40,700 --> 01:04:43,820 In February 25, 1990, she went into a coma, and then a 1473 01:04:43,820 --> 01:04:44,750 vegetative state. 1474 01:04:44,750 --> 01:04:47,860 So a vegetative state is when a person seems to be kind of 1475 01:04:47,860 --> 01:04:50,430 awake, but when you talk with them, they're not very aware, 1476 01:04:50,430 --> 01:04:51,990 they're not responsive, they're not noticing, they're 1477 01:04:51,990 --> 01:04:52,270 not talking. 1478 01:04:52,270 --> 01:04:54,230 But their eyes are open, and they're awake, their eyes are 1479 01:04:54,230 --> 01:04:57,040 not closed, so that's what she is. 1480 01:04:57,040 --> 01:04:59,650 And they put in her a feeding tube, because without that she 1481 01:04:59,650 --> 01:05:04,580 wouldn't live, she couldn't eat and feed herself. 1482 01:05:04,580 --> 01:05:07,270 It was a heartbreaking difference of opinion between 1483 01:05:07,270 --> 01:05:09,510 her husband and her parents. 1484 01:05:09,510 --> 01:05:13,460 Her husband petitioned some years later, actually eight 1485 01:05:13,460 --> 01:05:15,680 years later, to remove the feeding tube and 1486 01:05:15,680 --> 01:05:17,330 let her pass away. 1487 01:05:17,330 --> 01:05:19,750 The parents opposed that, they said that's not her wishes, 1488 01:05:19,750 --> 01:05:21,730 she would want to keep on going with the feeding tube. 1489 01:05:21,730 --> 01:05:23,620 The husband said no, I don't believe that's her wishes. 1490 01:05:23,620 --> 01:05:26,950 So you have this very tragic confrontation between the 1491 01:05:26,950 --> 01:05:29,350 parents who loved her, and the husband who presumably loved 1492 01:05:29,350 --> 01:05:33,270 her having different ideas about what to do with her, 1493 01:05:33,270 --> 01:05:35,440 whether to end her life or not. 1494 01:05:35,440 --> 01:05:38,470 So finally her tube was removed, but then the parents 1495 01:05:38,470 --> 01:05:40,770 went to court, and a judge reversed it, and they 1496 01:05:40,770 --> 01:05:41,820 put the tube back. 1497 01:05:41,820 --> 01:05:45,850 She became, sadly, kind of back and forth, living 1498 01:05:45,850 --> 01:05:48,220 nonliving, on judicial decisions. 1499 01:05:48,220 --> 01:05:51,630 Her case became particularly famous, for a bunch of 1500 01:05:51,630 --> 01:05:55,290 reasons, and it went back and forth from court, to court. 1501 01:05:55,290 --> 01:05:58,440 Moving up in the state courts, and there were several US 1502 01:05:58,440 --> 01:06:02,590 Supreme Court decisions about whether to remove the tube, or 1503 01:06:02,590 --> 01:06:03,980 keep the tube in. 1504 01:06:03,980 --> 01:06:06,520 And it's a tragic thing, it's a tragic choice between the 1505 01:06:06,520 --> 01:06:07,860 parents and the husband. 1506 01:06:07,860 --> 01:06:10,170 It got to the US Congress, in the US Senate. 1507 01:06:10,170 --> 01:06:14,840 President Bush signed a bill to keep her alive. 1508 01:06:14,840 --> 01:06:18,380 Everybody got involved, with various opinions, finally the 1509 01:06:18,380 --> 01:06:21,520 Supreme Court made a series of decisions. 1510 01:06:21,520 --> 01:06:23,680 It was disconnected in 2005, and she died in 1511 01:06:23,680 --> 01:06:25,200 March 31 of that year. 1512 01:06:25,200 --> 01:06:28,450 So tragic difficult decision, and a tragic family situation 1513 01:06:28,450 --> 01:06:30,180 that became kind of a political, 1514 01:06:30,180 --> 01:06:32,260 and judicial football. 1515 01:06:32,260 --> 01:06:34,610 So what's going on in the mind of somebody like this, and how 1516 01:06:34,610 --> 01:06:37,215 could we even begin to interpret it for a person who 1517 01:06:37,215 --> 01:06:40,620 can't speak for themselves and can't respond. 1518 01:06:40,620 --> 01:06:41,760 So let me tell you about a different case, we 1519 01:06:41,760 --> 01:06:43,790 don't know her case. 1520 01:06:43,790 --> 01:06:48,640 So, again a vegetative state is one where you appear to be 1521 01:06:48,640 --> 01:06:50,100 awake, but there's no sign of awareness. 1522 01:06:50,100 --> 01:06:51,790 Eyes are open, but the person's not talking or 1523 01:06:51,790 --> 01:06:53,300 responding to anything in their environment. 1524 01:06:53,300 --> 01:06:56,700 So here's a different woman, 23 years old, in 2005 she had 1525 01:06:56,700 --> 01:06:59,460 a road traffic accident, severe traumatic brain injury. 1526 01:06:59,460 --> 01:07:02,120 Five months later she's un-responsive, but she has 1527 01:07:02,120 --> 01:07:03,970 preserved sleep-wake, like she's waking up going to 1528 01:07:03,970 --> 01:07:04,930 sleep, waking up going to sleep. 1529 01:07:04,930 --> 01:07:09,650 Eyes open, but un-responsive in every other way. 1530 01:07:09,650 --> 01:07:12,810 They put her into an fMRI scanner, as well as healthy 1531 01:07:12,810 --> 01:07:15,550 comparison people, and they have them do to 1532 01:07:15,550 --> 01:07:19,060 mental imagery tasks. 1533 01:07:19,060 --> 01:07:21,130 they read instructions to her. 1534 01:07:21,130 --> 01:07:24,940 But you go into scanner, and you're told to imagine two 1535 01:07:24,940 --> 01:07:26,300 different things. 1536 01:07:26,300 --> 01:07:30,120 Playing tennis, so imagine in your mind's eye you playing 1537 01:07:30,120 --> 01:07:32,040 tennis for a moment, imagine that. 1538 01:07:32,040 --> 01:07:34,880 Or imagine visiting all the rooms of your house starting 1539 01:07:34,880 --> 01:07:37,790 with your front door, in the house that you are living in 1540 01:07:37,790 --> 01:07:38,930 now, or where you grew up. 1541 01:07:38,930 --> 01:07:40,870 Imagine those two things in your mind. 1542 01:07:40,870 --> 01:07:42,820 First of all, just a pure cognitive neuroscience level, 1543 01:07:42,820 --> 01:07:45,250 and we'll come back to that, imagination is a really 1544 01:07:45,250 --> 01:07:46,480 interesting thing. 1545 01:07:46,480 --> 01:07:50,290 And it turns out when we imagine things, again we use 1546 01:07:50,290 --> 01:07:52,340 the parts of our brain that does them, imagination is 1547 01:07:52,340 --> 01:07:53,820 perception run backwards. 1548 01:07:53,820 --> 01:07:56,700 We can see imagination in the human brain. 1549 01:07:56,700 --> 01:07:58,680 And depending on what you're imagining, you use the same 1550 01:07:58,680 --> 01:08:00,570 systems that you see with. 1551 01:08:00,570 --> 01:08:02,610 If you imagine something you're looking at, it will 1552 01:08:02,610 --> 01:08:04,120 turn on your visual system, it's even more 1553 01:08:04,120 --> 01:08:05,590 specific than that. 1554 01:08:05,590 --> 01:08:08,500 So let's first look at what happens with the controls. 1555 01:08:08,500 --> 01:08:10,810 When they imagine they're playing tennis, they turn on 1556 01:08:10,810 --> 01:08:14,010 the supplementary motor area, that's a part of your brain 1557 01:08:14,010 --> 01:08:16,960 that plans your physical movements. 1558 01:08:16,960 --> 01:08:19,830 You're not moving, but you're thinking about it, this is 1559 01:08:19,830 --> 01:08:21,640 imagination of movement. 1560 01:08:21,640 --> 01:08:24,120 When you plan a movement., you turn that on. 1561 01:08:24,120 --> 01:08:26,819 When you go around your house, you turn on spatial areas that 1562 01:08:26,819 --> 01:08:30,529 are in the parahippocampal cortex, and similar areas, 1563 01:08:30,529 --> 01:08:32,710 parietal cortex, and parahippocampal cortex. 1564 01:08:32,710 --> 01:08:35,080 They're turned on if we show you a movie where you're 1565 01:08:35,080 --> 01:08:36,189 moving around in spaces. 1566 01:08:36,189 --> 01:08:39,479 If you see spaces, you turn those on, if you imagine 1567 01:08:39,479 --> 01:08:40,439 spaces, you turn them on. 1568 01:08:40,439 --> 01:08:44,229 So imagination in the brain is perception run backwards, or 1569 01:08:44,229 --> 01:08:47,640 physical action run backwards, you're not actually doing it. 1570 01:08:47,640 --> 01:08:50,050 But look at this patient who got in the scanner, who was 1571 01:08:50,050 --> 01:08:53,910 non responsive, you read her the instructions, and see what 1572 01:08:53,910 --> 01:08:56,500 she does, and look at her brain. 1573 01:08:56,500 --> 01:08:59,859 Asked to imagine tennis, asked to imagine the 1574 01:08:59,859 --> 01:09:01,270 rooms in her house. 1575 01:09:01,270 --> 01:09:02,920 It looks just like that. 1576 01:09:02,920 --> 01:09:04,569 What does that mean, just in a common sense, 1577 01:09:04,569 --> 01:09:07,260 what does that mean? 1578 01:09:07,260 --> 01:09:10,319 Did she understand the instruction, at some level 1579 01:09:10,319 --> 01:09:14,279 yes, she wouldn't turn on those parts of the brain if 1580 01:09:14,279 --> 01:09:18,335 she didn't understand the instruction, she imagines the 1581 01:09:18,335 --> 01:09:20,950 thing you ask her to instruct. 1582 01:09:20,950 --> 01:09:22,340 So this guy on the front page of the New York Times said 1583 01:09:22,340 --> 01:09:25,310 fMRI could tell you the internal mental life of a 1584 01:09:25,310 --> 01:09:27,609 person could no longer speak, or communicate 1585 01:09:27,609 --> 01:09:29,470 with any other way. 1586 01:09:29,470 --> 01:09:33,270 Now it's turned out since then, that when they put in 1587 01:09:33,270 --> 01:09:35,490 other patients into the scanner, most of them don't 1588 01:09:35,490 --> 01:09:37,170 show this pattern. 1589 01:09:37,170 --> 01:09:40,830 So it's not that every patient in a vegetative state this is 1590 01:09:40,830 --> 01:09:43,149 full of mental life like this person. 1591 01:09:43,149 --> 01:09:45,359 And a deeper way, we don't really understand what this 1592 01:09:45,359 --> 01:09:46,740 mental life is like. 1593 01:09:46,740 --> 01:09:49,422 We don't know whether she simply understands some 1594 01:09:49,422 --> 01:09:51,899 things, but doesn't have feelings, or plans, or 1595 01:09:51,899 --> 01:09:53,830 desires, or whether she has those too. 1596 01:09:53,830 --> 01:09:56,860 We don't understand really the full range of mental life, but 1597 01:09:56,860 --> 01:09:59,950 we know that she can understand an instruction, and 1598 01:09:59,950 --> 01:10:01,760 her brain follows through with it. 1599 01:10:01,760 --> 01:10:04,480 Most patients, it turns out, don't look like that in 1600 01:10:04,480 --> 01:10:05,850 vegetative states. 1601 01:10:05,850 --> 01:10:08,840 So again, brain imaging has taken us inside the mind of 1602 01:10:08,840 --> 01:10:11,120 somebody who cannot communicate for themselves and 1603 01:10:11,120 --> 01:10:13,060 let us say something about what it is that's 1604 01:10:13,060 --> 01:10:15,340 going on in that mind. 1605 01:10:15,340 --> 01:10:17,800 In conclusion, we've talked about different ways of 1606 01:10:17,800 --> 01:10:20,680 learning about the brain, different methods to record 1607 01:10:20,680 --> 01:10:22,920 structure and function that vary in their temporal and 1608 01:10:22,920 --> 01:10:24,280 spatial acuity. 1609 01:10:24,280 --> 01:10:28,480 And incredibly different ways in which we can understand the 1610 01:10:28,480 --> 01:10:31,190 organization in time and space of how the brain supports the 1611 01:10:31,190 --> 01:10:32,440 human mind.