1 00:00:00,000 --> 00:00:04,780 [LOGO SOUNDS] 2 00:00:10,000 --> 00:00:12,500 NANCY KANWISHER: So I'm doing another one of these big mongo 3 00:00:12,500 --> 00:00:13,875 lectures that takes a whole week, 4 00:00:13,875 --> 00:00:16,755 so this is really a continuation of last time. 5 00:00:16,755 --> 00:00:18,380 This is the outline for the whole week. 6 00:00:18,380 --> 00:00:21,920 We got through most of the stuff on face perception. 7 00:00:21,920 --> 00:00:23,360 I'll do some more today. 8 00:00:23,360 --> 00:00:25,200 We're right there. 9 00:00:25,200 --> 00:00:27,590 And we're going to go on and consider this question of, 10 00:00:27,590 --> 00:00:30,800 what's innate, and how do you wire up brains? 11 00:00:30,800 --> 00:00:35,540 So first, a brief recap of main points from last time. 12 00:00:35,540 --> 00:00:38,510 What, if anything, is innate about face perception? 13 00:00:38,510 --> 00:00:41,360 We considered lots of different kinds of evidence, behavioral 14 00:00:41,360 --> 00:00:42,290 and neural. 15 00:00:42,290 --> 00:00:46,130 And the bottom line is, maybe not that much. 16 00:00:46,130 --> 00:00:49,280 So there's a few things that are sort of suggestive, 17 00:00:49,280 --> 00:00:52,190 like newborns have this bias to look at faces more 18 00:00:52,190 --> 00:00:54,050 than other non-face stimuli that are 19 00:00:54,050 --> 00:00:56,900 pretty similar-- schematic faces versus scrambled schematic 20 00:00:56,900 --> 00:00:57,740 faces. 21 00:00:57,740 --> 00:00:59,300 And that's suggestive. 22 00:00:59,300 --> 00:01:01,520 But then there's the possibility that that's 23 00:01:01,520 --> 00:01:04,190 just due to some very, very simple property 24 00:01:04,190 --> 00:01:06,680 of those stimuli, namely just having more junk 25 00:01:06,680 --> 00:01:09,890 on the top than the bottom, like eyes on the top than bottom. 26 00:01:09,890 --> 00:01:11,750 So what would have to be innate in that case 27 00:01:11,750 --> 00:01:15,200 would be just the simplest possible template, not even 28 00:01:15,200 --> 00:01:17,200 a whole face. 29 00:01:17,200 --> 00:01:18,950 Similarly, we showed that there's actually 30 00:01:18,950 --> 00:01:21,290 very good discrimination of one face from another, 31 00:01:21,290 --> 00:01:25,820 even across viewpoint changes in newborn humans, 32 00:01:25,820 --> 00:01:29,780 and also in monkeys that were raised without ever 33 00:01:29,780 --> 00:01:32,120 being allowed to see faces. 34 00:01:32,120 --> 00:01:36,260 And both of those things suggest innate abilities 35 00:01:36,260 --> 00:01:39,510 to process faces, but in both cases, 36 00:01:39,510 --> 00:01:43,100 it's possible to argue that that ability isn't due to face 37 00:01:43,100 --> 00:01:44,820 mechanisms in particular. 38 00:01:44,820 --> 00:01:47,750 It's due to just general vision and shape perception. 39 00:01:50,900 --> 00:01:53,870 Third, I showed you beautiful recent data 40 00:01:53,870 --> 00:01:56,870 showing that the face patches in monkeys 41 00:01:56,870 --> 00:01:58,820 don't develop if monkeys are reared 42 00:01:58,820 --> 00:02:00,440 without ever seeing faces. 43 00:02:03,140 --> 00:02:06,470 Which also suggests that maybe not that much is innate. 44 00:02:06,470 --> 00:02:09,229 So all that is fine, but then there's 45 00:02:09,229 --> 00:02:12,020 a big, wide open question that's left 46 00:02:12,020 --> 00:02:13,820 unanswered by all of that, which is, 47 00:02:13,820 --> 00:02:18,890 how do the face areas know to land right there in everybody, 48 00:02:18,890 --> 00:02:20,090 robustly? 49 00:02:20,090 --> 00:02:22,010 That really feels like something has 50 00:02:22,010 --> 00:02:25,050 to be innate about the brain, at least, 51 00:02:25,050 --> 00:02:27,710 to say where those things should go. 52 00:02:27,710 --> 00:02:30,620 OK, so one possibility that I'm sort of skipping over, 53 00:02:30,620 --> 00:02:32,240 because it's a whole little universe, 54 00:02:32,240 --> 00:02:34,550 and there isn't an answer yet-- people are working on it right 55 00:02:34,550 --> 00:02:36,925 now, people in this building are working on it right now, 56 00:02:36,925 --> 00:02:43,220 but the gist of the idea is that maybe what's innate 57 00:02:43,220 --> 00:02:46,070 is some other kind of simpler selectivity. 58 00:02:46,070 --> 00:02:48,500 Maybe like selectivity for curved things. 59 00:02:48,500 --> 00:02:51,350 Remember how I talked about, as you go up the visual system, 60 00:02:51,350 --> 00:02:55,430 you start with selectivity for spots of light and then edges? 61 00:02:55,430 --> 00:02:56,930 Well, maybe up there, you're born 62 00:02:56,930 --> 00:02:59,120 with selectivity for curved things, 63 00:02:59,120 --> 00:03:01,820 or something like that, that is face-like enough 64 00:03:01,820 --> 00:03:04,520 that somehow that leads face selectivity to land 65 00:03:04,520 --> 00:03:05,262 there later. 66 00:03:05,262 --> 00:03:07,220 It's kind of vague because nobody really knows, 67 00:03:07,220 --> 00:03:09,710 but that's an idea. 68 00:03:09,710 --> 00:03:12,500 Another possibility that we'll talk more about in a moment 69 00:03:12,500 --> 00:03:15,540 is a possibility that the reason your face patches land right 70 00:03:15,540 --> 00:03:18,260 there is something about the long-range structural 71 00:03:18,260 --> 00:03:20,720 connectivity of that region to the rest of the brain 72 00:03:20,720 --> 00:03:22,920 makes that the right place. 73 00:03:22,920 --> 00:03:25,640 And so all of this is very actively being investigated, 74 00:03:25,640 --> 00:03:28,190 and nobody knows the right answer here. 75 00:03:28,190 --> 00:03:32,630 Further, I just want to mention that deep net modeling is just 76 00:03:32,630 --> 00:03:35,870 very suddenly in the last year become a very powerful way 77 00:03:35,870 --> 00:03:38,940 to approach these same questions from a different angle. 78 00:03:38,940 --> 00:03:42,890 So with deep nets, you can ask, what do you 79 00:03:42,890 --> 00:03:47,840 need to build into a network to get it to produce face patches? 80 00:03:47,840 --> 00:03:51,020 So that's a way of asking, in principle, 81 00:03:51,020 --> 00:03:53,510 in a network where you can actually control everything 82 00:03:53,510 --> 00:03:57,110 about its architecture and about the stimuli it sees, 83 00:03:57,110 --> 00:03:59,330 what are the necessary conditions for it to produce 84 00:03:59,330 --> 00:04:01,880 something like face patches? 85 00:04:01,880 --> 00:04:03,950 What do you have to train it on to get 86 00:04:03,950 --> 00:04:07,790 it to produce face patches, and to be able to recognize faces? 87 00:04:07,790 --> 00:04:11,420 And at the top level, why, computationally, does it 88 00:04:11,420 --> 00:04:13,980 make sense to have face patches in the first place? 89 00:04:13,980 --> 00:04:15,530 This is kind of the biggest question 90 00:04:15,530 --> 00:04:17,447 lurking in the background of this whole field. 91 00:04:17,447 --> 00:04:20,060 I'm describing all of these specialized mechanisms 92 00:04:20,060 --> 00:04:22,310 in mind and brain, but really, wouldn't it 93 00:04:22,310 --> 00:04:25,100 be nice to know why our minds and brains are organized 94 00:04:25,100 --> 00:04:27,680 that way, rather than just that they are? 95 00:04:27,680 --> 00:04:29,100 And that's a really hard question, 96 00:04:29,100 --> 00:04:30,710 and I think there's a real hope now 97 00:04:30,710 --> 00:04:34,220 that computational modeling may get us toward an answer 98 00:04:34,220 --> 00:04:38,750 sometime in the next decade, maybe even the next few years. 99 00:04:38,750 --> 00:04:40,880 OK, so that's the overview. 100 00:04:40,880 --> 00:04:45,140 I now want to go on quite a discussion about this notion 101 00:04:45,140 --> 00:04:48,530 that preexisting connectivity may be a major constraint 102 00:04:48,530 --> 00:04:50,820 in wiring up the brain. 103 00:04:50,820 --> 00:04:52,910 So first, we need to talk about, how 104 00:04:52,910 --> 00:04:55,760 would you look at structural connectivity in human brains? 105 00:04:55,760 --> 00:04:57,560 And I haven't really talked about this yet. 106 00:04:57,560 --> 00:05:00,320 The main method for being able to look-- 107 00:05:00,320 --> 00:05:03,650 for being able to get some sense of this in human brains 108 00:05:03,650 --> 00:05:06,230 is to use another kind of MRI imaging. 109 00:05:06,230 --> 00:05:08,660 Uses the same machine that's an MRI machine, 110 00:05:08,660 --> 00:05:11,830 but it's going to produce anatomical images that show us 111 00:05:11,830 --> 00:05:14,620 not those nice pretty pictures of brains that you're used to, 112 00:05:14,620 --> 00:05:19,090 but that show us the direction of water diffusion. 113 00:05:19,090 --> 00:05:21,520 And so the principle is pretty simple. 114 00:05:21,520 --> 00:05:26,140 Here is a picture of an optic tract. 115 00:05:26,140 --> 00:05:28,930 And what it's showing you is that if you see, 116 00:05:28,930 --> 00:05:31,240 an optic tract is a whole bunch of axons 117 00:05:31,240 --> 00:05:35,950 oriented like this connecting retinal ganglion cells to what? 118 00:05:38,560 --> 00:05:40,420 Where do the retinal ganglion cell axons 119 00:05:40,420 --> 00:05:42,880 land going through the optic tract? 120 00:05:42,880 --> 00:05:43,420 [INAUDIBLE] 121 00:05:43,420 --> 00:05:44,650 AUDIENCE: LOG? 122 00:05:44,650 --> 00:05:45,760 NANCY KANWISHER: LGN. 123 00:05:45,760 --> 00:05:46,330 LGN. 124 00:05:46,330 --> 00:05:48,670 Lateral geniculate nucleus of the thalamus. 125 00:05:48,670 --> 00:05:50,230 So there's that fiber bundle. 126 00:05:50,230 --> 00:05:52,900 But the main point for now is that you 127 00:05:52,900 --> 00:05:55,240 can see that each of those fibers 128 00:05:55,240 --> 00:05:58,480 has a layer of fat around it, and the upshot of all of that 129 00:05:58,480 --> 00:06:00,580 is that water likes to diffuse more 130 00:06:00,580 --> 00:06:03,400 in this direction than that direction. 131 00:06:03,400 --> 00:06:05,800 That's the key idea of diffusion imaging. 132 00:06:05,800 --> 00:06:09,730 It tells you which direction water is diffusing most. 133 00:06:09,730 --> 00:06:13,690 Water is constrained by the fat layers around those axons, 134 00:06:13,690 --> 00:06:14,650 that myelin. 135 00:06:14,650 --> 00:06:16,690 And so you get diffusion more in this direction 136 00:06:16,690 --> 00:06:18,800 than orthogonally to it. 137 00:06:18,800 --> 00:06:22,690 And so the details of the physics 138 00:06:22,690 --> 00:06:25,810 of this kind of imaging, which I'm totally not explaining, 139 00:06:25,810 --> 00:06:28,930 are such that what you get out is 140 00:06:28,930 --> 00:06:31,750 a picture at each point in the brain of what 141 00:06:31,750 --> 00:06:35,837 is the direction of maximum diffusion at that point. 142 00:06:35,837 --> 00:06:37,420 And so here's a little picture of lots 143 00:06:37,420 --> 00:06:39,950 of little vectors saying, at this point, 144 00:06:39,950 --> 00:06:41,920 water wants to diffuse this way, or this way, 145 00:06:41,920 --> 00:06:43,300 or this way, or this way. 146 00:06:43,300 --> 00:06:44,600 Everybody with me so far? 147 00:06:44,600 --> 00:06:46,660 So you get a whole bunch of little teeny vectors 148 00:06:46,660 --> 00:06:49,960 all through the brain showing you the orientation where water 149 00:06:49,960 --> 00:06:51,880 wants to diffuse at that point. 150 00:06:51,880 --> 00:06:54,550 And the idea is that's telling us 151 00:06:54,550 --> 00:06:57,610 which way fibers are going at that point. 152 00:06:57,610 --> 00:06:59,590 And we can therefore infer-- 153 00:06:59,590 --> 00:07:03,850 we can follow these things using a method called tractography, 154 00:07:03,850 --> 00:07:05,650 where we just follow those little vectors 155 00:07:05,650 --> 00:07:06,490 through the brain. 156 00:07:06,490 --> 00:07:07,823 And that's what's happened here. 157 00:07:07,823 --> 00:07:10,150 At each point in the brain, you start at one point, 158 00:07:10,150 --> 00:07:14,050 and you just follow these vectors and see where they go. 159 00:07:14,050 --> 00:07:16,833 Does that make sense, sort of intuitively? 160 00:07:16,833 --> 00:07:18,250 I'm skipping over lots of details, 161 00:07:18,250 --> 00:07:20,470 but I want you to get the gist. 162 00:07:20,470 --> 00:07:24,910 OK, so these beautiful pictures that you may have seen before 163 00:07:24,910 --> 00:07:26,800 are diffusion tractography. 164 00:07:26,800 --> 00:07:32,140 They show you our best guess of the long-range connections 165 00:07:32,140 --> 00:07:34,600 between one part of the brain and another 166 00:07:34,600 --> 00:07:37,690 based on diffusion tractography. 167 00:07:37,690 --> 00:07:39,610 And on the theory that you should 168 00:07:39,610 --> 00:07:42,800 wear your data whenever possible, 169 00:07:42,800 --> 00:07:44,110 here's mine from my lab. 170 00:07:44,110 --> 00:07:46,610 Whoops, I'm tangling it here. 171 00:07:46,610 --> 00:07:49,480 So-- I love these things, they're so beautiful. 172 00:07:49,480 --> 00:07:52,562 One of my post-docs who's our tractography whiz 173 00:07:52,562 --> 00:07:53,770 gave me this beautiful scarf. 174 00:07:53,770 --> 00:07:54,700 Isn't this nice? 175 00:07:54,700 --> 00:07:57,040 And so you can see even more clearly here 176 00:07:57,040 --> 00:08:00,370 that this is a cross-section through the brain in this axis 177 00:08:00,370 --> 00:08:01,460 right here. 178 00:08:01,460 --> 00:08:05,950 And so these big green guys are the connections 179 00:08:05,950 --> 00:08:08,583 that go from the back of the head down the temporal lobe, 180 00:08:08,583 --> 00:08:10,000 down the visual pathway that we've 181 00:08:10,000 --> 00:08:12,130 been talking about all along. 182 00:08:12,130 --> 00:08:13,850 OK, that was gratuitous. 183 00:08:13,850 --> 00:08:16,210 I just thought it was fun. 184 00:08:16,210 --> 00:08:18,280 OK, so tractography is cool. 185 00:08:18,280 --> 00:08:20,440 It makes gorgeous pictures and gorgeous scarves. 186 00:08:23,800 --> 00:08:26,798 And it works really well to discover big fiber bundles. 187 00:08:26,798 --> 00:08:28,840 There are lots of parts of the brain I showed you 188 00:08:28,840 --> 00:08:30,550 with that gross dissection picture 189 00:08:30,550 --> 00:08:32,770 last time, that there are big chunks of white matter 190 00:08:32,770 --> 00:08:35,500 where lots and lots of parallel fibers go like this. 191 00:08:35,500 --> 00:08:38,140 And tractography works well to find those. 192 00:08:38,140 --> 00:08:41,840 You can really see those very nicely with diffusion imaging. 193 00:08:41,840 --> 00:08:47,500 However, it's not so hot for discovering finer connections. 194 00:08:47,500 --> 00:08:49,630 It's better than nothing, but there's 195 00:08:49,630 --> 00:08:52,370 a lot of ways in which it fails. 196 00:08:52,370 --> 00:08:54,440 So for example, if you have water-- 197 00:08:54,440 --> 00:08:56,260 if you have fibers crossing in some part 198 00:08:56,260 --> 00:08:58,840 of the brain like this, you'll get diffusion 199 00:08:58,840 --> 00:09:00,700 in this direction and this direction, 200 00:09:00,700 --> 00:09:02,737 and the tractography algorithm will be finished. 201 00:09:02,737 --> 00:09:04,570 It won't know whether to keep going straight 202 00:09:04,570 --> 00:09:06,460 or whether to turn. 203 00:09:06,460 --> 00:09:08,080 So that's just one of many reasons why 204 00:09:08,080 --> 00:09:11,170 diffusion tractography is lovely, and wonderful, 205 00:09:11,170 --> 00:09:16,340 and the best we have in in-vivo brains, but it's not so great. 206 00:09:16,340 --> 00:09:19,780 Anyway, it's all we have, so we use it. 207 00:09:19,780 --> 00:09:20,530 OK. 208 00:09:20,530 --> 00:09:25,510 So we can use tractography to ask, for example, 209 00:09:25,510 --> 00:09:28,420 is the long-range connectivity of the fusiform face 210 00:09:28,420 --> 00:09:31,690 area distinct from the long-range connectivity 211 00:09:31,690 --> 00:09:33,340 of its neighbors? 212 00:09:33,340 --> 00:09:36,760 In other words, on this idea that that patch of cortex 213 00:09:36,760 --> 00:09:40,390 gets wired up to be a face area, somehow because 214 00:09:40,390 --> 00:09:44,230 of the connectivity to and from that region 215 00:09:44,230 --> 00:09:47,327 to other parts of the brain, then we 216 00:09:47,327 --> 00:09:48,910 should predict that that region should 217 00:09:48,910 --> 00:09:51,700 have different connectivity than neighboring cortex. 218 00:09:51,700 --> 00:09:54,280 Otherwise, connectivity isn't enough of a signature 219 00:09:54,280 --> 00:09:56,680 to tell us where to put a face area. 220 00:09:56,680 --> 00:09:57,850 I'm seeing blank looks. 221 00:09:57,850 --> 00:09:59,050 Is this not making sense? 222 00:09:59,050 --> 00:10:00,190 OK. 223 00:10:00,190 --> 00:10:03,490 Just butt in and ask questions if I'm not making sense. 224 00:10:03,490 --> 00:10:04,180 OK. 225 00:10:04,180 --> 00:10:08,260 So question is, do these connectivity fingerprints 226 00:10:08,260 --> 00:10:11,680 predict the location of functional regions, first 227 00:10:11,680 --> 00:10:12,830 in adults? 228 00:10:12,830 --> 00:10:15,270 If we don't see it in adults, then the jig's up. 229 00:10:15,270 --> 00:10:17,080 So let's start with adults. 230 00:10:17,080 --> 00:10:17,740 OK. 231 00:10:17,740 --> 00:10:21,490 So the way that you can do this is, for each voxel 232 00:10:21,490 --> 00:10:22,310 in the brain-- 233 00:10:22,310 --> 00:10:23,880 this is a big one, so you can see it. 234 00:10:23,880 --> 00:10:25,630 It would actually be a couple millimeters, 235 00:10:25,630 --> 00:10:27,100 wouldn't show on this picture. 236 00:10:27,100 --> 00:10:30,650 What you do is you follow that tractography and you say, 237 00:10:30,650 --> 00:10:35,590 oh, look, it went there, and it goes there, and it goes there. 238 00:10:35,590 --> 00:10:39,170 And you tally how often, when you start here, 239 00:10:39,170 --> 00:10:43,340 you land in each of a bunch of different big anatomical chunks 240 00:10:43,340 --> 00:10:44,810 of brain. 241 00:10:44,810 --> 00:10:48,050 That gives you a description of the connectivity fingerprint 242 00:10:48,050 --> 00:10:49,220 of that voxel. 243 00:10:49,220 --> 00:10:51,230 How strong is its connection to each 244 00:10:51,230 --> 00:10:54,590 of these other remote regions in the brain? 245 00:10:54,590 --> 00:10:57,410 That's what I mean by a connectivity fingerprint. 246 00:10:57,410 --> 00:11:00,440 So now the question is, can you use 247 00:11:00,440 --> 00:11:05,750 this connectivity fingerprint to predict what 248 00:11:05,750 --> 00:11:07,631 the function of that voxel is? 249 00:11:07,631 --> 00:11:10,700 That is, is the connectivity distinctive enough that, 250 00:11:10,700 --> 00:11:13,370 just based on diffusion data, we could 251 00:11:13,370 --> 00:11:15,800 say, what does that voxel do? 252 00:11:15,800 --> 00:11:19,550 If the fusiform face area has a whole distinctive connectivity 253 00:11:19,550 --> 00:11:22,020 fingerprint, then we should be able to predict it. 254 00:11:22,020 --> 00:11:23,550 Does this make sense? 255 00:11:23,550 --> 00:11:24,950 OK, so that's the question. 256 00:11:24,950 --> 00:11:26,900 And there's a lot of math, which I'll skip. 257 00:11:26,900 --> 00:11:28,430 I'll just give you the gist. 258 00:11:28,430 --> 00:11:30,013 So what we're trying to figure out is, 259 00:11:30,013 --> 00:11:32,450 is the fusiform face area distinct from its neighbors 260 00:11:32,450 --> 00:11:33,920 in its long-range connectivity? 261 00:11:33,920 --> 00:11:36,290 That's the question. 262 00:11:36,290 --> 00:11:37,850 And, in fact, it is. 263 00:11:37,850 --> 00:11:39,140 And we can show that. 264 00:11:39,140 --> 00:11:40,790 Again, I'm skipping over some details, 265 00:11:40,790 --> 00:11:44,840 but here is a recently-published paper that shows you 266 00:11:44,840 --> 00:11:46,550 in ways that should be familiar now, 267 00:11:46,550 --> 00:11:49,310 this is functional MRI activation 268 00:11:49,310 --> 00:11:50,990 for faces versus objects. 269 00:11:50,990 --> 00:11:52,940 Fusiform face area, that's probably 270 00:11:52,940 --> 00:11:55,910 occipital face area, another region we'll talk about later. 271 00:11:55,910 --> 00:11:56,840 The face patches. 272 00:11:56,840 --> 00:11:58,040 The usual face patches. 273 00:11:58,040 --> 00:11:59,863 Again, this is an inflated brain, 274 00:11:59,863 --> 00:12:01,280 so the dark bits are the bits that 275 00:12:01,280 --> 00:12:03,110 used to be folded up inside the sulcus 276 00:12:03,110 --> 00:12:06,020 until they were mathematically inflated. 277 00:12:06,020 --> 00:12:08,510 So that's the standard thing we've been looking at. 278 00:12:08,510 --> 00:12:12,980 This is the prediction based on diffusion tractography 279 00:12:12,980 --> 00:12:16,820 alone in the same subject about where the face patches should 280 00:12:16,820 --> 00:12:17,750 be. 281 00:12:17,750 --> 00:12:21,620 So very roughly, what you do is you take some other subjects, 282 00:12:21,620 --> 00:12:24,230 and you train them up on connectivity fingerprints-- 283 00:12:24,230 --> 00:12:28,520 it's kind of like NVPA, but you train from diffusion data, 284 00:12:28,520 --> 00:12:31,340 and you try to predict face selectivity. 285 00:12:31,340 --> 00:12:34,340 And then you take the diffusion data from a new subject, 286 00:12:34,340 --> 00:12:37,580 and you predict where that face selectivity should be, 287 00:12:37,580 --> 00:12:40,220 and there's where it's predicted for the same subject, 288 00:12:40,220 --> 00:12:42,380 and it's pretty damn good. 289 00:12:42,380 --> 00:12:44,943 Did everybody get the gist of what I just went through? 290 00:12:44,943 --> 00:12:46,610 You don't need to remember every detail. 291 00:12:46,610 --> 00:12:50,300 The key idea is, is there a systematic relationship 292 00:12:50,300 --> 00:12:52,640 between long-range connectivity of a voxel 293 00:12:52,640 --> 00:12:55,010 and its function, its selectivity? 294 00:12:55,010 --> 00:12:58,340 And this says yes for faces. 295 00:12:58,340 --> 00:12:58,940 OK? 296 00:12:58,940 --> 00:13:00,470 So that's the case for faces. 297 00:13:00,470 --> 00:13:02,870 That tells us that in adults, those face regions 298 00:13:02,870 --> 00:13:05,512 have distinct connectivity. 299 00:13:05,512 --> 00:13:06,470 This is the same thing. 300 00:13:06,470 --> 00:13:08,450 I just shrunk it so I could fit in other stuff. 301 00:13:08,450 --> 00:13:11,390 Here is doing the same thing for scenes. 302 00:13:11,390 --> 00:13:16,220 Functional selectivity PPA RSC, functional selectivity 303 00:13:16,220 --> 00:13:18,680 for scenes measured with functional MRI, 304 00:13:18,680 --> 00:13:22,250 predicted functional pattern from the same subject 305 00:13:22,250 --> 00:13:25,190 with just tractography alone. 306 00:13:25,190 --> 00:13:27,322 OK? 307 00:13:27,322 --> 00:13:28,280 Do you have a question? 308 00:13:28,280 --> 00:13:29,096 AUDIENCE: Oh, no. 309 00:13:29,096 --> 00:13:29,929 [INTERPOSING VOICES] 310 00:13:29,929 --> 00:13:31,763 NANCY KANWISHER: It's pretty good, isn't it? 311 00:13:31,763 --> 00:13:32,300 Yeah, yeah. 312 00:13:32,300 --> 00:13:33,500 No, I was dissing diffusion. 313 00:13:33,500 --> 00:13:36,360 You might be thinking, OK, I was dissing diffusion tractography. 314 00:13:36,360 --> 00:13:36,860 It sucks. 315 00:13:36,860 --> 00:13:37,943 It has all these problems. 316 00:13:37,943 --> 00:13:39,330 It has all these ambiguities. 317 00:13:39,330 --> 00:13:41,090 So how could it work so well? 318 00:13:41,090 --> 00:13:42,060 That's a good question. 319 00:13:42,060 --> 00:13:43,260 I don't know the answer to that. 320 00:13:43,260 --> 00:13:44,760 I think in part, it's because you're 321 00:13:44,760 --> 00:13:47,610 predicting based on all of these different connections. 322 00:13:47,610 --> 00:13:49,760 So even if half of them are wrong, 323 00:13:49,760 --> 00:13:52,110 you can still get some predictive power out of it. 324 00:13:52,110 --> 00:13:53,860 That's just my guess. 325 00:13:53,860 --> 00:13:54,670 OK? 326 00:13:54,670 --> 00:13:56,500 OK, so it works pretty well for scenes, 327 00:13:56,500 --> 00:13:58,960 and it works pretty well for body selectivity as well. 328 00:13:58,960 --> 00:14:03,790 Functional MRI prediction from connectivity. 329 00:14:03,790 --> 00:14:05,470 So that's cool. 330 00:14:05,470 --> 00:14:08,080 So that says, these all have distinct connectivity 331 00:14:08,080 --> 00:14:11,890 fingerprints, but now this is all done in adults. 332 00:14:11,890 --> 00:14:17,290 And remember, the way we got into this long shaggy dog story 333 00:14:17,290 --> 00:14:20,740 is to ask what these long-range connections, what role they 334 00:14:20,740 --> 00:14:22,450 might play in development. 335 00:14:22,450 --> 00:14:24,880 Remember that I said last time that most 336 00:14:24,880 --> 00:14:28,940 of the long-range connections of the brain are present at birth. 337 00:14:28,940 --> 00:14:32,950 So that suggests that maybe these connections are also 338 00:14:32,950 --> 00:14:33,820 there at birth. 339 00:14:36,460 --> 00:14:38,980 And it suggests that maybe indeed those connections could 340 00:14:38,980 --> 00:14:40,150 play a role in development. 341 00:14:40,150 --> 00:14:41,485 At least they're probably there. 342 00:14:41,485 --> 00:14:45,250 They're in a position to play that role, 343 00:14:45,250 --> 00:14:48,110 if that's actually what happens. 344 00:14:48,110 --> 00:14:54,815 So all of this brings us to the case of rewired ferrets. 345 00:14:54,815 --> 00:14:55,315 What? 346 00:14:55,315 --> 00:14:56,350 What am I talking about? 347 00:14:56,350 --> 00:14:57,970 They're cute, aren't they? 348 00:14:57,970 --> 00:15:00,220 They're also very good experimental animals 349 00:15:00,220 --> 00:15:02,600 to address just this question. 350 00:15:02,600 --> 00:15:04,260 And Mriganka Sur in this department 351 00:15:04,260 --> 00:15:08,290 did this very important paper a while back 352 00:15:08,290 --> 00:15:12,792 where he asked whether connectivity instructs 353 00:15:12,792 --> 00:15:13,750 functional development. 354 00:15:13,750 --> 00:15:17,350 That is, whether the connectivity present at birth 355 00:15:17,350 --> 00:15:21,130 is sufficient to determine the function of the region that 356 00:15:21,130 --> 00:15:22,450 has those connections. 357 00:15:22,450 --> 00:15:26,350 And he did this by manipulating connectivity. 358 00:15:26,350 --> 00:15:28,450 So if you want to ask, what is the causal role 359 00:15:28,450 --> 00:15:30,610 of x, you have to manipulate x. 360 00:15:30,610 --> 00:15:32,740 So we've talked a lot about this in this class. 361 00:15:32,740 --> 00:15:34,060 Functional MRI, wonderful. 362 00:15:34,060 --> 00:15:34,810 You see activity. 363 00:15:34,810 --> 00:15:38,150 You have no idea what its causal role is until you mess with it. 364 00:15:38,150 --> 00:15:40,690 For example, by electrically stimulating the brain. 365 00:15:40,690 --> 00:15:44,260 Similarly, connectivity may be present at birth, 366 00:15:44,260 --> 00:15:47,118 and may predict where we may be able to use it to predict 367 00:15:47,118 --> 00:15:48,160 where the functions land. 368 00:15:48,160 --> 00:15:50,290 It doesn't tell us that it's playing a causal role. 369 00:15:50,290 --> 00:15:52,390 The way to find out if it's playing a causal role 370 00:15:52,390 --> 00:15:54,740 is to change it and see what happens. 371 00:15:54,740 --> 00:15:57,640 And that's what Mriganka Sur and his colleagues did. 372 00:15:57,640 --> 00:16:02,350 So they used ferrets because they're born very prematurely. 373 00:16:02,350 --> 00:16:06,010 And so what that means is that you can operate on them 374 00:16:06,010 --> 00:16:09,460 surgically right at birth before they 375 00:16:09,460 --> 00:16:10,672 have any visual experience. 376 00:16:10,672 --> 00:16:12,130 They haven't opened their eyes yet. 377 00:16:12,130 --> 00:16:14,260 And you can-- turns out-- reroute 378 00:16:14,260 --> 00:16:15,850 some of the connectivity. 379 00:16:15,850 --> 00:16:20,050 OK, so this is a diagram of some bits that should be familiar. 380 00:16:20,050 --> 00:16:22,870 The retina going to the lateral geniculate nucleus and then 381 00:16:22,870 --> 00:16:23,920 up to V1. 382 00:16:23,920 --> 00:16:26,350 Also true in ferrets. 383 00:16:26,350 --> 00:16:29,530 In addition, we have primary auditory cortex that we'll 384 00:16:29,530 --> 00:16:31,600 talk more about in a few weeks. 385 00:16:31,600 --> 00:16:33,820 So just like V1, but for hearing. 386 00:16:33,820 --> 00:16:34,704 A1. 387 00:16:34,704 --> 00:16:38,510 A1 also goes to another nucleus in the thalamus. 388 00:16:38,510 --> 00:16:40,840 This one called the medial geniculate nucleus. 389 00:16:40,840 --> 00:16:43,420 And then it goes from there up through a complicated chain, 390 00:16:43,420 --> 00:16:46,300 eventually-- oh, sorry, it goes this way. 391 00:16:46,300 --> 00:16:49,090 Thalamus up to A1. 392 00:16:49,090 --> 00:16:54,010 So that's the basic wiring of an adult ferret. 393 00:16:54,010 --> 00:16:56,830 And so what Sur and his colleagues 394 00:16:56,830 --> 00:16:58,660 figured out how to do is redirect 395 00:16:58,660 --> 00:17:02,420 some of those connections by surgery at birth. 396 00:17:02,420 --> 00:17:05,619 So this is a wiring diagram of the same thing shown here. 397 00:17:05,619 --> 00:17:08,050 Retina, LGN. 398 00:17:08,050 --> 00:17:10,359 This is V1, it's also called 17. 399 00:17:10,359 --> 00:17:13,690 And here is medial geniculate and auditory cortex. 400 00:17:13,690 --> 00:17:19,720 And so what they did was to surgically knock out 401 00:17:19,720 --> 00:17:27,430 a few of these connections here in the just-born ferret pups. 402 00:17:27,430 --> 00:17:30,850 And what happens is if you knock out this connection 403 00:17:30,850 --> 00:17:34,900 here, the fibers that start this way get rerouted, 404 00:17:34,900 --> 00:17:38,920 and you end up with a ferret that's wired up like this. 405 00:17:38,920 --> 00:17:42,790 The important part of this is this rewired ferret 406 00:17:42,790 --> 00:17:47,920 has a connection between their retina and medial geniculate 407 00:17:47,920 --> 00:17:50,690 nucleus that goes to primary auditory cortex. 408 00:17:50,690 --> 00:17:52,960 So we're taking visual input at the periphery 409 00:17:52,960 --> 00:17:56,770 and wiring it up into the auditory system. 410 00:17:56,770 --> 00:18:00,760 And the point of all of this is now, 411 00:18:00,760 --> 00:18:03,700 primary auditory cortex in this developing ferret 412 00:18:03,700 --> 00:18:06,320 will be getting visual input. 413 00:18:06,320 --> 00:18:10,420 And so if the input were sufficient to determine 414 00:18:10,420 --> 00:18:13,810 the function of that region of cortex, then 415 00:18:13,810 --> 00:18:15,850 what should we find in these rewired ferrets? 416 00:18:15,850 --> 00:18:20,300 What should happen in what would have been primary auditory 417 00:18:20,300 --> 00:18:20,800 cortex? 418 00:18:20,800 --> 00:18:22,660 What should it do? 419 00:18:22,660 --> 00:18:23,661 Christine. 420 00:18:27,098 --> 00:18:29,062 AUDIENCE: [INAUDIBLE] visual-- 421 00:18:29,062 --> 00:18:30,130 NANCY KANWISHER: Yeah! 422 00:18:30,130 --> 00:18:32,800 It should behave like visual cortex, absolutely. 423 00:18:32,800 --> 00:18:34,690 If everything's determined by the inputs, 424 00:18:34,690 --> 00:18:38,440 we change the inputs, it should behave like visual cortex. 425 00:18:38,440 --> 00:18:41,020 Well, that would be freaking crazy, wouldn't it? 426 00:18:41,020 --> 00:18:42,760 I mean, it's miles away in the brain. 427 00:18:42,760 --> 00:18:44,980 It's a totally different part of brain. 428 00:18:44,980 --> 00:18:47,870 That will be nuts. 429 00:18:47,870 --> 00:18:49,500 But that's what happens. 430 00:18:49,500 --> 00:18:50,410 It's pretty amazing. 431 00:18:50,410 --> 00:18:52,270 This is a really important study. 432 00:18:52,270 --> 00:18:53,820 OK. 433 00:18:53,820 --> 00:18:56,100 All right. 434 00:18:56,100 --> 00:18:58,950 So what you find, first of all, is 435 00:18:58,950 --> 00:19:02,010 that primary auditory cortex in the rewired ferrets 436 00:19:02,010 --> 00:19:04,500 responds to visual input. 437 00:19:04,500 --> 00:19:05,040 That's cool. 438 00:19:05,040 --> 00:19:07,340 But you might say, OK, you wired visual input in there. 439 00:19:07,340 --> 00:19:09,340 Of course it's going to respond to visual input. 440 00:19:09,340 --> 00:19:12,540 So maybe that's not too cool, but not too surprising. 441 00:19:12,540 --> 00:19:15,990 But the next part is really cool and really surprising. 442 00:19:15,990 --> 00:19:22,020 Remember how I said that in normal visual cortex-- 443 00:19:22,020 --> 00:19:24,390 in humans and monkeys, and also ferrets-- 444 00:19:24,390 --> 00:19:26,770 you get these orientation columns. 445 00:19:26,770 --> 00:19:28,320 Now, remember, these are-- 446 00:19:28,320 --> 00:19:32,610 what this shows is that as you move across the cortex in V1-- 447 00:19:32,610 --> 00:19:35,640 we're now talking visual cortex here-- in visual cortex, 448 00:19:35,640 --> 00:19:39,600 in normal mammals, you get this smooth progression 449 00:19:39,600 --> 00:19:42,202 of orientation selectivity as you move across the cortex. 450 00:19:42,202 --> 00:19:43,410 And that's what's shown here. 451 00:19:43,410 --> 00:19:44,670 Everybody with the program? 452 00:19:44,670 --> 00:19:45,420 OK. 453 00:19:45,420 --> 00:19:50,400 So that's normal primary visual cortex in an adult animal. 454 00:19:50,400 --> 00:19:53,520 What do you think primary auditory cortex looks 455 00:19:53,520 --> 00:19:55,770 like in the rewired ferrets? 456 00:19:55,770 --> 00:19:57,570 Damn similar. 457 00:19:57,570 --> 00:20:01,200 So not only do you get visual responses 458 00:20:01,200 --> 00:20:04,380 in what would have been auditory cortex when you rewire, 459 00:20:04,380 --> 00:20:06,000 you get orientation columns. 460 00:20:06,000 --> 00:20:08,550 You get this really fine-grained structure 461 00:20:08,550 --> 00:20:10,500 of what everybody thought this was 462 00:20:10,500 --> 00:20:12,240 something about visual cortex. 463 00:20:12,240 --> 00:20:14,190 Well, this says that visual input 464 00:20:14,190 --> 00:20:17,220 is sufficient to produce orientation columns 465 00:20:17,220 --> 00:20:19,110 in a part of cortex that otherwise never 466 00:20:19,110 --> 00:20:21,430 would have had them. 467 00:20:21,430 --> 00:20:24,090 Does everybody see how mind-blowing this is? 468 00:20:24,090 --> 00:20:25,140 OK. 469 00:20:25,140 --> 00:20:27,030 So that's pretty cool, but now we 470 00:20:27,030 --> 00:20:29,370 get to the really cool question. 471 00:20:29,370 --> 00:20:34,290 When these neurons are active, does the ferret see, 472 00:20:34,290 --> 00:20:37,380 or do they hear? 473 00:20:37,380 --> 00:20:38,220 OK. 474 00:20:38,220 --> 00:20:39,150 It's rewired. 475 00:20:39,150 --> 00:20:40,950 It's getting input from the retina, 476 00:20:40,950 --> 00:20:42,480 but there's neurons in what would 477 00:20:42,480 --> 00:20:44,970 have been primary auditory cortex now 478 00:20:44,970 --> 00:20:46,930 responding to visual input. 479 00:20:46,930 --> 00:20:49,780 What does the ferret think is going on? 480 00:20:49,780 --> 00:20:52,560 Does he say, oh, that's sight, because he's 481 00:20:52,560 --> 00:20:55,080 learned that visual input means that's sight? 482 00:20:55,080 --> 00:20:57,750 Or does he say, I hear something, 483 00:20:57,750 --> 00:21:01,470 because that's auditory cortex. 484 00:21:01,470 --> 00:21:04,530 Everybody in the grip of what a cool question that is? 485 00:21:04,530 --> 00:21:05,040 OK. 486 00:21:05,040 --> 00:21:07,080 And so it could go either way. 487 00:21:07,080 --> 00:21:08,880 There's really no way to tell in advance. 488 00:21:08,880 --> 00:21:12,150 It depends on how you read out the information 489 00:21:12,150 --> 00:21:13,410 in that piece of cortex. 490 00:21:13,410 --> 00:21:17,100 When we do NVPA, we sit god-like by, 491 00:21:17,100 --> 00:21:19,982 and we look at a patch of brain, and we decode what's in there. 492 00:21:19,982 --> 00:21:21,690 But really, what's happening in the brain 493 00:21:21,690 --> 00:21:24,450 is some other part of the brain is getting input, and decoding, 494 00:21:24,450 --> 00:21:25,657 and interpreting it. 495 00:21:25,657 --> 00:21:27,990 And so the question is, what do later parts of the brain 496 00:21:27,990 --> 00:21:29,910 make of this? 497 00:21:29,910 --> 00:21:31,380 And the answer is the later parts 498 00:21:31,380 --> 00:21:34,080 of the brain learn that that's visual information, 499 00:21:34,080 --> 00:21:38,383 and the ferret reports seeing stuff, not hearing it. 500 00:21:38,383 --> 00:21:40,800 Now, you may be thinking, how the hell do you ask a ferret 501 00:21:40,800 --> 00:21:43,050 if he's seeing or hearing? 502 00:21:43,050 --> 00:21:45,780 What you do is you use non-rewired parts 503 00:21:45,780 --> 00:21:47,625 of the same ferret's brain. 504 00:21:47,625 --> 00:21:49,500 Actually, forget if it's the other hemisphere 505 00:21:49,500 --> 00:21:51,510 or a different part of the visual field 506 00:21:51,510 --> 00:21:53,610 that doesn't get rewired. 507 00:21:53,610 --> 00:21:57,597 So you have gold standard, where normal vision is working, 508 00:21:57,597 --> 00:21:59,430 and normal hearing is working in the ferret, 509 00:21:59,430 --> 00:22:01,890 and you train him, press this button when you see 510 00:22:01,890 --> 00:22:04,380 and press this button when you hear, and it's unambiguous. 511 00:22:04,380 --> 00:22:08,550 And then once he's trained, you stimulate those A1 neurons 512 00:22:08,550 --> 00:22:12,690 and you ask him what's going on, and he says he sees something. 513 00:22:12,690 --> 00:22:14,320 OK? 514 00:22:14,320 --> 00:22:18,520 All right, so this is one of the true classics. 515 00:22:18,520 --> 00:22:20,170 OK. 516 00:22:20,170 --> 00:22:25,540 So this means that A1 in this case, primary auditory cortex, 517 00:22:25,540 --> 00:22:28,090 is instructed by its connectivity 518 00:22:28,090 --> 00:22:31,690 and by the experience that comes through that connectivity 519 00:22:31,690 --> 00:22:33,880 to shape its function. 520 00:22:33,880 --> 00:22:35,140 Everybody got that? 521 00:22:35,140 --> 00:22:36,850 All right. 522 00:22:36,850 --> 00:22:39,190 So both experience and connectivity 523 00:22:39,190 --> 00:22:44,150 can determine cortical function, at least in ferrets. 524 00:22:44,150 --> 00:22:44,650 What? 525 00:22:44,650 --> 00:22:45,390 Yes, question. 526 00:22:45,390 --> 00:22:46,682 AUDIENCE: I have two questions. 527 00:22:46,682 --> 00:22:49,870 So first of all, what does their V1 look 528 00:22:49,870 --> 00:22:52,960 like after this rewiring, and also, can they hear things, 529 00:22:52,960 --> 00:22:54,033 and if so, where is it? 530 00:22:54,033 --> 00:22:55,450 NANCY KANWISHER: Yeah, absolutely. 531 00:22:55,450 --> 00:22:59,420 OK, so if you look at the diagram, there is additional-- 532 00:22:59,420 --> 00:23:01,780 well, actually, it's not in the diagram. 533 00:23:01,780 --> 00:23:06,680 But there is additional input that's not shown here. 534 00:23:06,680 --> 00:23:09,730 So they can hear things through maybe the other hemisphere, 535 00:23:09,730 --> 00:23:10,360 I forget. 536 00:23:10,360 --> 00:23:12,260 They can hear. 537 00:23:12,260 --> 00:23:15,548 And they can see, because notice-- 538 00:23:15,548 --> 00:23:16,090 that's right. 539 00:23:16,090 --> 00:23:18,910 OK, we blocked off area 17, but these guys 540 00:23:18,910 --> 00:23:20,810 are higher-level visual areas. 541 00:23:20,810 --> 00:23:23,950 So they can see both through their non-rewired hemisphere 542 00:23:23,950 --> 00:23:26,290 and through some other bypassing connections 543 00:23:26,290 --> 00:23:28,810 to other parts of visual cortex. 544 00:23:28,810 --> 00:23:31,150 Probably, both of those are going to be affected. 545 00:23:31,150 --> 00:23:34,300 Your vision is going to be different if you bypass V1. 546 00:23:34,300 --> 00:23:37,090 But there will be at least some visual information. 547 00:23:39,750 --> 00:23:41,820 OK, so that's ferrets. 548 00:23:41,820 --> 00:23:45,000 Again, animals, you can do invasive studies 549 00:23:45,000 --> 00:23:47,010 and really do the strong manipulation 550 00:23:47,010 --> 00:23:49,440 to do a strong test of a causal role, 551 00:23:49,440 --> 00:23:51,540 and this is a classic example. 552 00:23:51,540 --> 00:23:53,430 Of course, we can't rewire humans-- 553 00:23:53,430 --> 00:23:56,010 or we could, but it wouldn't be nice. 554 00:23:56,010 --> 00:23:58,950 But really, we want to know, how does all that stuff get 555 00:23:58,950 --> 00:24:00,000 wired up? 556 00:24:00,000 --> 00:24:01,830 Are these regions also-- 557 00:24:01,830 --> 00:24:04,740 is their function determined by their connectivity 558 00:24:04,740 --> 00:24:10,980 present at birth, and due to the experience of those 559 00:24:10,980 --> 00:24:12,370 regions have? 560 00:24:12,370 --> 00:24:12,870 OK. 561 00:24:12,870 --> 00:24:17,460 Well, we can't do controlled rearing studies in humans. 562 00:24:17,460 --> 00:24:19,600 We can't rewire their brains. 563 00:24:19,600 --> 00:24:23,380 But we can be clever and smart and think of other cases. 564 00:24:23,380 --> 00:24:25,800 So here's an important test case. 565 00:24:25,800 --> 00:24:30,120 The important test case is the case of reading. 566 00:24:30,120 --> 00:24:31,620 Why reading? 567 00:24:31,620 --> 00:24:34,800 Well, one, we all spend a lot of time doing it. 568 00:24:34,800 --> 00:24:38,220 And two, humans have only been reading for a few thousand 569 00:24:38,220 --> 00:24:39,690 years. 570 00:24:39,690 --> 00:24:42,300 And that's not long enough for natural selection 571 00:24:42,300 --> 00:24:45,000 to have crafted an innately-specified circuit just 572 00:24:45,000 --> 00:24:46,560 for reading. 573 00:24:46,560 --> 00:24:50,460 So that means that if we did find a patch of cortex that 574 00:24:50,460 --> 00:24:53,550 responds selectively to visually-presented words, 575 00:24:53,550 --> 00:24:58,020 or letters, that would suggest that for that case at least, 576 00:24:58,020 --> 00:25:00,570 experience was sufficient to wire up, 577 00:25:00,570 --> 00:25:04,090 to determine the function of that region of cortex. 578 00:25:04,090 --> 00:25:05,340 This is all very hypothetical. 579 00:25:05,340 --> 00:25:07,020 Everybody got the idea? 580 00:25:07,020 --> 00:25:07,740 OK. 581 00:25:07,740 --> 00:25:10,980 Now, notice, this does not apply to hearing words. 582 00:25:10,980 --> 00:25:13,380 People have been hearing words for hundreds of thousands 583 00:25:13,380 --> 00:25:14,880 of years, perhaps millions. 584 00:25:14,880 --> 00:25:18,450 And so that's plenty of time for special purpose circuitry, 585 00:25:18,450 --> 00:25:21,780 and that special purpose circuitry exists 586 00:25:21,780 --> 00:25:24,210 and we'll talk about it in a month or so. 587 00:25:24,210 --> 00:25:26,550 But now we're talking about the case of visual word 588 00:25:26,550 --> 00:25:30,870 recognition-- this recent cultural invention of humans. 589 00:25:30,870 --> 00:25:33,120 So that's why it's a special case, because we know 590 00:25:33,120 --> 00:25:35,370 that's too recent to be innate. 591 00:25:35,370 --> 00:25:38,820 And so if we find a selectivity, it can't be innate. 592 00:25:38,820 --> 00:25:40,080 All right? 593 00:25:40,080 --> 00:25:42,900 So that's what I just said. 594 00:25:42,900 --> 00:25:45,250 So do we have such a thing? 595 00:25:45,250 --> 00:25:46,890 Well, how would you test for it? 596 00:25:46,890 --> 00:25:48,940 What would you do? 597 00:25:48,940 --> 00:25:52,092 Joseph, what would you do? 598 00:25:52,092 --> 00:25:53,300 You want to know if there's-- 599 00:26:00,050 --> 00:26:01,940 AUDIENCE: I guess I would show them words, 600 00:26:01,940 --> 00:26:04,113 and then show them not words, and see-- 601 00:26:04,113 --> 00:26:05,030 NANCY KANWISHER: Yeah. 602 00:26:05,030 --> 00:26:07,220 It's not rocket science, guys. 603 00:26:07,220 --> 00:26:08,900 We just keep doing the same damn thing. 604 00:26:08,900 --> 00:26:10,070 Exactly. 605 00:26:10,070 --> 00:26:11,570 Right. 606 00:26:11,570 --> 00:26:14,850 So start by-- here's what we did. 607 00:26:14,850 --> 00:26:17,420 We showed people visually-presented words 608 00:26:17,420 --> 00:26:20,390 like that, and we showed them line drawings of objects. 609 00:26:23,180 --> 00:26:27,110 And when we did that, we found that in most subjects, 610 00:26:27,110 --> 00:26:29,450 there's a tiny little patch of the bottom 611 00:26:29,450 --> 00:26:31,402 of their left hemisphere right near the zones 612 00:26:31,402 --> 00:26:32,860 we've been talking about, near face 613 00:26:32,860 --> 00:26:35,400 selective and other regions on the bottom of the brain. 614 00:26:35,400 --> 00:26:39,800 But that tiny little patch responds significantly more 615 00:26:39,800 --> 00:26:42,500 to words than pictures. 616 00:26:45,320 --> 00:26:47,780 Now, we won't do this now, but you can do it 617 00:26:47,780 --> 00:26:50,090 as a thought experiment. 618 00:26:50,090 --> 00:26:52,880 What are the alternative accounts of that activation? 619 00:26:52,880 --> 00:26:55,100 Has this shown that that region is selectively 620 00:26:55,100 --> 00:26:56,720 involved in reading? 621 00:26:56,720 --> 00:26:58,290 Of course not. 622 00:26:58,290 --> 00:27:00,520 There's a million differences between-- 623 00:27:03,170 --> 00:27:06,320 oh, come on-- these and those. 624 00:27:06,320 --> 00:27:08,300 How bright they are, how big they are. 625 00:27:08,300 --> 00:27:10,370 It's a million differences. 626 00:27:10,370 --> 00:27:11,940 And so to get serious about it, we 627 00:27:11,940 --> 00:27:13,940 have to do the same game that we've been playing 628 00:27:13,940 --> 00:27:15,030 all along in this course. 629 00:27:15,030 --> 00:27:16,430 This is like a first whack at it. 630 00:27:16,430 --> 00:27:18,290 You find something, now we have a candidate. 631 00:27:18,290 --> 00:27:19,910 But if we want to get serious, we've 632 00:27:19,910 --> 00:27:21,577 got to test some other conditions to see 633 00:27:21,577 --> 00:27:23,060 if that's really for real. 634 00:27:23,060 --> 00:27:24,290 OK? 635 00:27:24,290 --> 00:27:25,040 All right. 636 00:27:25,040 --> 00:27:27,870 So here's what we did in my lab when we did this a while back. 637 00:27:27,870 --> 00:27:31,340 So first of all, this is left-out data. 638 00:27:31,340 --> 00:27:33,350 Once you find that region-- remember, 639 00:27:33,350 --> 00:27:35,840 if you're trying to characterize the function of a region, 640 00:27:35,840 --> 00:27:38,060 I talked briefly about this, a good way 641 00:27:38,060 --> 00:27:40,850 to do it is to run a localizer to find 642 00:27:40,850 --> 00:27:42,290 that region in each subject. 643 00:27:42,290 --> 00:27:43,290 Now we found it. 644 00:27:43,290 --> 00:27:44,540 Now we have those voxels. 645 00:27:44,540 --> 00:27:46,763 Now we collect some new data that may 646 00:27:46,763 --> 00:27:47,930 be a lot like our localizer. 647 00:27:47,930 --> 00:27:48,680 It doesn't matter. 648 00:27:48,680 --> 00:27:52,280 We collect some new data and we look at the response. 649 00:27:52,280 --> 00:27:55,260 And that just puts us on stronger statistical footing. 650 00:27:55,260 --> 00:27:55,760 OK. 651 00:27:55,760 --> 00:27:57,830 So here is time going this way. 652 00:27:57,830 --> 00:28:00,230 This is something called an event-related design, where 653 00:28:00,230 --> 00:28:03,050 you just present a single stimulus, and then wait, 654 00:28:03,050 --> 00:28:05,480 and another stimulus rather than a whole bunch of them 655 00:28:05,480 --> 00:28:07,460 mushed together in a block. 656 00:28:07,460 --> 00:28:09,950 And then you average over many, many repetitions. 657 00:28:09,950 --> 00:28:12,710 And so this is the response over time-- it's seconds, 658 00:28:12,710 --> 00:28:14,570 it's really slow-- 659 00:28:14,570 --> 00:28:17,832 to words and line drawings in that region. 660 00:28:17,832 --> 00:28:20,040 So this is just replicating what I showed you before. 661 00:28:20,040 --> 00:28:22,550 It's showing you what the actual selectivity 662 00:28:22,550 --> 00:28:27,860 looks like in the real data, not just in a significance map. 663 00:28:27,860 --> 00:28:31,590 Why is this thing taking six seconds to respond? 664 00:28:31,590 --> 00:28:33,050 This is stimulus onset out there. 665 00:28:38,680 --> 00:28:39,370 Yes. 666 00:28:39,370 --> 00:28:42,730 AUDIENCE: That's the time between blood flow? 667 00:28:42,730 --> 00:28:43,660 NANCY KANWISHER: Yeah. 668 00:28:43,660 --> 00:28:45,250 Remember, the signal we're looking at 669 00:28:45,250 --> 00:28:46,420 is based on blood flow. 670 00:28:46,420 --> 00:28:48,092 The neurons all fired right here, 671 00:28:48,092 --> 00:28:50,300 but it takes a while to get the blood flow to change. 672 00:28:50,300 --> 00:28:51,300 That's why it's delayed. 673 00:28:51,300 --> 00:28:52,510 Exactly. 674 00:28:52,510 --> 00:28:53,240 OK. 675 00:28:53,240 --> 00:28:53,740 All right. 676 00:28:53,740 --> 00:28:55,250 So what else are we going to test? 677 00:28:55,250 --> 00:28:57,122 Well, you can do lots of different things. 678 00:28:57,122 --> 00:28:58,330 We just tried lots of things. 679 00:28:58,330 --> 00:29:00,970 We said, OK, let's have other things that are symbols 680 00:29:00,970 --> 00:29:02,450 but that our subjects can't read. 681 00:29:02,450 --> 00:29:06,370 So we tried Chinese characters, low response. 682 00:29:06,370 --> 00:29:07,840 We tried digit strings. 683 00:29:07,840 --> 00:29:09,040 Pretty low response. 684 00:29:09,040 --> 00:29:11,800 That's pretty remarkable, because words and digit strings 685 00:29:11,800 --> 00:29:14,480 are pretty similar in how we use them and what they look like. 686 00:29:14,480 --> 00:29:15,397 So that's pretty good. 687 00:29:17,800 --> 00:29:22,840 We tried consonant strings, like this, that you can't pronounce. 688 00:29:22,840 --> 00:29:25,150 And we got the same response. 689 00:29:25,150 --> 00:29:26,330 And this is important. 690 00:29:26,330 --> 00:29:31,360 It tells us this region is not a word region. 691 00:29:31,360 --> 00:29:34,550 Instead, it's something about recognizing letters. 692 00:29:34,550 --> 00:29:37,240 But for the purposes of the current argument, that's OK. 693 00:29:37,240 --> 00:29:41,470 It's still something that has no basis in human evolution, 694 00:29:41,470 --> 00:29:44,530 and so if we find selectivity for letters that are presumably 695 00:29:44,530 --> 00:29:46,660 used in the process of reading, that 696 00:29:46,660 --> 00:29:49,380 must have come from experience. 697 00:29:49,380 --> 00:29:51,600 OK? 698 00:29:51,600 --> 00:29:52,500 What else did we do? 699 00:29:52,500 --> 00:29:54,810 OK, that's what I just said. 700 00:29:54,810 --> 00:29:58,530 Now, I submit that this is a pretty good argument 701 00:29:58,530 --> 00:30:02,130 that that region must have been wired up by experience. 702 00:30:02,130 --> 00:30:03,510 But you could niggle. 703 00:30:03,510 --> 00:30:08,250 You could say, well, there are more straight edges 704 00:30:08,250 --> 00:30:09,810 with the words and consonants. 705 00:30:09,810 --> 00:30:11,760 The digits are curvier, or whatever. 706 00:30:11,760 --> 00:30:13,950 You could make up some story about how 707 00:30:13,950 --> 00:30:18,690 that isn't necessarily selective for letters and words, 708 00:30:18,690 --> 00:30:21,540 and therefore, maybe it's not necessarily 709 00:30:21,540 --> 00:30:23,550 wired up by experience. 710 00:30:23,550 --> 00:30:26,040 Further, who knows? 711 00:30:26,040 --> 00:30:28,890 Maybe everybody just has that weird selectivity in there 712 00:30:28,890 --> 00:30:32,820 even if they never learned to read. 713 00:30:32,820 --> 00:30:36,270 So it would really be nice to make a stronger case. 714 00:30:36,270 --> 00:30:39,600 And what we did was we couldn't find people in Cambridge 715 00:30:39,600 --> 00:30:43,200 who couldn't read, who didn't have other things going on, 716 00:30:43,200 --> 00:30:48,360 but we could find people who did read Hebrew. 717 00:30:48,360 --> 00:30:50,310 And we had-- where's my Hebrew data? 718 00:30:50,310 --> 00:30:51,300 All right, hang on. 719 00:30:51,300 --> 00:30:52,440 OK, right. 720 00:30:52,440 --> 00:30:55,110 So here are our non-Hebrew readers. 721 00:30:57,617 --> 00:30:58,200 This is funny. 722 00:30:58,200 --> 00:30:59,490 This is an old graph. 723 00:30:59,490 --> 00:31:02,430 It's not so impressive-looking. 724 00:31:02,430 --> 00:31:05,640 This is-- I forgot to switch out our newer data. 725 00:31:05,640 --> 00:31:09,000 OK, so what we found is in people who don't read Hebrew, 726 00:31:09,000 --> 00:31:11,642 the response was lower to Hebrew than to words. 727 00:31:11,642 --> 00:31:13,350 Looks like it's almost as high, actually. 728 00:31:13,350 --> 00:31:16,530 When we ran more subjects, it's actually quite a bit lower. 729 00:31:16,530 --> 00:31:18,390 Nonetheless, when we ran people who 730 00:31:18,390 --> 00:31:22,360 read both English and Hebrew, the Hebrew response is higher. 731 00:31:22,360 --> 00:31:26,520 And that nails the case that it's actually that individual's 732 00:31:26,520 --> 00:31:29,620 experience that determines the selectivity of this region. 733 00:31:29,620 --> 00:31:31,500 It depends on what orthographies you know. 734 00:31:31,500 --> 00:31:33,900 If you know how to read Hebrew, you get a high response. 735 00:31:33,900 --> 00:31:35,940 If you don't, you get a lower response. 736 00:31:35,940 --> 00:31:39,210 Everybody get that this pretty much nails the case? 737 00:31:39,210 --> 00:31:41,160 OK, so where are we? 738 00:31:41,160 --> 00:31:44,040 All of this was to say, do we ever 739 00:31:44,040 --> 00:31:49,243 see selectivity in the brain that can't be innate? 740 00:31:49,243 --> 00:31:51,660 And I submit to you, this is selectivity in the brain that 741 00:31:51,660 --> 00:31:54,300 can't be innate, that has to be learned. 742 00:31:54,300 --> 00:31:56,280 And in fact, our data show that it depends 743 00:31:56,280 --> 00:31:59,220 on the subject's experience. 744 00:31:59,220 --> 00:32:00,450 OK. 745 00:32:00,450 --> 00:32:03,210 So-- good. 746 00:32:03,210 --> 00:32:05,950 So yes, we have such a thing. 747 00:32:05,950 --> 00:32:09,450 It's called the visual word form area. 748 00:32:09,450 --> 00:32:14,520 Now, what about this idea that connectivity of that region 749 00:32:14,520 --> 00:32:17,730 is playing a role-- it's in a very systematic location. 750 00:32:17,730 --> 00:32:20,550 It's that little orange thing right there. 751 00:32:20,550 --> 00:32:21,358 Yes, question. 752 00:32:21,358 --> 00:32:22,150 AUDIENCE: Question. 753 00:32:22,150 --> 00:32:24,740 I'm just trying to think through the alternative. 754 00:32:24,740 --> 00:32:26,520 The brain has to be shaped by experience, 755 00:32:26,520 --> 00:32:28,425 otherwise you would never learn anything, right? 756 00:32:28,425 --> 00:32:29,130 NANCY KANWISHER: Absolutely. 757 00:32:29,130 --> 00:32:31,680 AUDIENCE: Even if this didn't show that difference, 758 00:32:31,680 --> 00:32:32,700 it would just mean the difference is 759 00:32:32,700 --> 00:32:33,750 something you're not measuring. 760 00:32:33,750 --> 00:32:35,640 NANCY KANWISHER: Absolutely, absolutely. 761 00:32:35,640 --> 00:32:38,325 You wouldn't be able to understand the sentence I'm 762 00:32:38,325 --> 00:32:40,200 saying right now without changing your brain, 763 00:32:40,200 --> 00:32:41,910 because by the time you get to the end of the sentence, 764 00:32:41,910 --> 00:32:43,500 you need to remember what I said at the beginning 765 00:32:43,500 --> 00:32:45,980 of the sentence, so there's little things structurally 766 00:32:45,980 --> 00:32:47,730 wiggling around in your brain and changing 767 00:32:47,730 --> 00:32:50,052 synaptic connectivity online all the time 768 00:32:50,052 --> 00:32:52,260 or you wouldn't be able to think, let alone remember. 769 00:32:52,260 --> 00:32:53,280 Absolutely. 770 00:32:53,280 --> 00:32:55,150 So the question here is more specific. 771 00:32:55,150 --> 00:32:58,230 It's not whether the brain changes with experience. 772 00:32:58,230 --> 00:32:59,700 Absolutely, it does. 773 00:32:59,700 --> 00:33:04,620 It's whether experience can explain these particular cell 774 00:33:04,620 --> 00:33:06,840 activities and where they came from. 775 00:33:06,840 --> 00:33:09,780 I'm glad you asked that question. 776 00:33:09,780 --> 00:33:11,040 OK. 777 00:33:11,040 --> 00:33:13,860 OK, so now, we've just argued that the selectivity 778 00:33:13,860 --> 00:33:16,685 of that little dot, at least, must be due to experience. 779 00:33:16,685 --> 00:33:18,060 Doesn't tell us about the others, 780 00:33:18,060 --> 00:33:19,560 but tells us that one must be. 781 00:33:19,560 --> 00:33:23,400 And now we're asking, can its selectivity-- 782 00:33:23,400 --> 00:33:27,780 can that location be determined by the connectivity 783 00:33:27,780 --> 00:33:30,890 of that region? 784 00:33:30,890 --> 00:33:35,330 So to get to that, we use diffusion tractography. 785 00:33:35,330 --> 00:33:37,670 And the hypothesis here is that it's 786 00:33:37,670 --> 00:33:40,040 these long-range connections that determine where 787 00:33:40,040 --> 00:33:42,410 those functional regions land. 788 00:33:42,410 --> 00:33:45,107 This is me with a bunch of functional regions in my head. 789 00:33:45,107 --> 00:33:46,190 Doesn't matter which ones. 790 00:33:46,190 --> 00:33:48,830 We're just asking the general question. 791 00:33:48,830 --> 00:33:50,960 And so I'm going to skip over all the details, 792 00:33:50,960 --> 00:33:52,993 but just give you the gist of a recent paper 793 00:33:52,993 --> 00:33:54,410 that we published looking at this. 794 00:33:54,410 --> 00:33:57,560 We asked-- we found the visual word form area. 795 00:33:57,560 --> 00:34:01,850 That's right down in there, about there, left hemisphere. 796 00:34:01,850 --> 00:34:08,150 And we scanned kids at age eight and age five, same kids. 797 00:34:08,150 --> 00:34:09,679 Age five, then age eight. 798 00:34:09,679 --> 00:34:11,810 Here's the age eight data. 799 00:34:11,810 --> 00:34:15,170 These kids have learned to read in between the two scans. 800 00:34:15,170 --> 00:34:17,900 And here is the response of their visual word form 801 00:34:17,900 --> 00:34:21,590 area to words, faces, objects, and scrambled objects. 802 00:34:21,590 --> 00:34:24,920 Nice and selective, just like a good visual word form 803 00:34:24,920 --> 00:34:27,230 area should respond. 804 00:34:27,230 --> 00:34:29,480 So it's there by age eight. 805 00:34:29,480 --> 00:34:32,659 What we then do is we take the data in the same kid 806 00:34:32,659 --> 00:34:36,320 across those three years, align the data, and say, 807 00:34:36,320 --> 00:34:39,920 what were those voxels doing in that kid at age five 808 00:34:39,920 --> 00:34:42,139 before they learned to read? 809 00:34:42,139 --> 00:34:43,969 This is another way of showing that it's 810 00:34:43,969 --> 00:34:45,650 experience that was necessary. 811 00:34:45,650 --> 00:34:48,409 And boom, they were not word selective. 812 00:34:48,409 --> 00:34:49,250 They shouldn't be. 813 00:34:49,250 --> 00:34:51,350 These kids hadn't learned to read yet. 814 00:34:51,350 --> 00:34:54,100 But it's still kind of nice to be able to show that. 815 00:34:54,100 --> 00:34:54,960 All right? 816 00:34:54,960 --> 00:34:59,040 But now, the hypothesis is that it's 817 00:34:59,040 --> 00:35:02,550 the connectivity at age five that predicts where 818 00:35:02,550 --> 00:35:04,630 this region is going to land. 819 00:35:04,630 --> 00:35:06,990 So we use that same rigmarole that I showed you 820 00:35:06,990 --> 00:35:11,190 earlier for adults, where we used just diffusion data 821 00:35:11,190 --> 00:35:14,580 to predict where the functional region will arise. 822 00:35:14,580 --> 00:35:18,060 But we use the diffusion data from five-year-olds 823 00:35:18,060 --> 00:35:19,890 to predict where that region would 824 00:35:19,890 --> 00:35:23,010 arise when the kids were eight. 825 00:35:23,010 --> 00:35:24,690 And it turns out you can do that. 826 00:35:24,690 --> 00:35:27,390 You can predict actually fine-grained individual 827 00:35:27,390 --> 00:35:30,300 differences in exactly where the visual word form 828 00:35:30,300 --> 00:35:33,810 area will arise at age eight from that same kid's 829 00:35:33,810 --> 00:35:37,740 connectivity at age five. 830 00:35:37,740 --> 00:35:39,330 So does everybody see how that fits 831 00:35:39,330 --> 00:35:41,820 one of the necessary conditions for this idea 832 00:35:41,820 --> 00:35:45,420 that the locations where these things land later 833 00:35:45,420 --> 00:35:48,150 in development is determined by connectivity 834 00:35:48,150 --> 00:35:50,140 that exists before? 835 00:35:50,140 --> 00:35:52,007 Now, our study was done in humans, 836 00:35:52,007 --> 00:35:53,340 so we didn't have a causal test. 837 00:35:53,340 --> 00:35:56,320 All we can say is it was there before, and it's sufficient. 838 00:35:56,320 --> 00:35:58,680 But we don't know if that's actually how it worked. 839 00:35:58,680 --> 00:36:00,820 That's how it is working on humans. 840 00:36:00,820 --> 00:36:02,820 But if you put it together with the ferret data, 841 00:36:02,820 --> 00:36:05,110 it's pretty suggestive. 842 00:36:05,110 --> 00:36:05,610 All right? 843 00:36:05,610 --> 00:36:06,420 Yeah. 844 00:36:06,420 --> 00:36:08,055 AUDIENCE: Where is it connected to? 845 00:36:08,055 --> 00:36:08,888 NANCY KANWISHER: Ah. 846 00:36:08,888 --> 00:36:09,690 Very good question. 847 00:36:09,690 --> 00:36:12,480 I'm being very vague, connectivity. 848 00:36:12,480 --> 00:36:15,180 This is a long, complicated issue. 849 00:36:15,180 --> 00:36:19,080 Most likely, it's connected to language-y areas, which we'll 850 00:36:19,080 --> 00:36:21,630 talk about in a month or so, that 851 00:36:21,630 --> 00:36:25,290 are out on the lateral surface and up in the frontal lobe. 852 00:36:25,290 --> 00:36:26,970 There are papers claiming that it's 853 00:36:26,970 --> 00:36:29,850 connected to language-y areas. 854 00:36:29,850 --> 00:36:32,010 But I'm kind of a methodological hard ass, 855 00:36:32,010 --> 00:36:33,900 and I don't quite believe those data. 856 00:36:33,900 --> 00:36:36,225 I mean, I think they have a medium case, 857 00:36:36,225 --> 00:36:37,350 but they haven't nailed it. 858 00:36:37,350 --> 00:36:38,550 I've tried to nail it. 859 00:36:38,550 --> 00:36:41,080 It's hard for all of the reasons that this method 860 00:36:41,080 --> 00:36:42,330 that I was complaining about-- 861 00:36:42,330 --> 00:36:45,150 I'm complaining about it because I'm bitter about it. 862 00:36:45,150 --> 00:36:46,580 I want this method to be better. 863 00:36:46,580 --> 00:36:49,080 I want to know what those actual structural connections are. 864 00:36:49,080 --> 00:36:54,270 I wish we could put a seed in the visual word form area 865 00:36:54,270 --> 00:36:56,305 and follow those tracks and say not just 866 00:36:56,305 --> 00:36:57,930 there's enough of a fingerprint that we 867 00:36:57,930 --> 00:37:02,190 can predict its function, but here are the exact connections. 868 00:37:02,190 --> 00:37:06,930 And it's, mm, not quite up to that task, in my view. 869 00:37:06,930 --> 00:37:08,990 It's a big bummer. 870 00:37:08,990 --> 00:37:11,490 I've wasted a lot of the last year trying to get that method 871 00:37:11,490 --> 00:37:15,540 to work, and I haven't quite given up yet, but I'm close. 872 00:37:15,540 --> 00:37:16,153 It's OK. 873 00:37:16,153 --> 00:37:18,570 It's just not good enough to answer those questions, which 874 00:37:18,570 --> 00:37:21,530 is very frustrating because they're pressing questions. 875 00:37:21,530 --> 00:37:22,030 Yeah. 876 00:37:22,030 --> 00:37:22,510 AUDIENCE: Can I ask one more question? 877 00:37:22,510 --> 00:37:23,427 NANCY KANWISHER: Yeah. 878 00:37:23,427 --> 00:37:26,880 AUDIENCE: So people who are blind shouldn't 879 00:37:26,880 --> 00:37:28,290 have this region active. 880 00:37:28,290 --> 00:37:30,290 NANCY KANWISHER: Ooh, very interesting question. 881 00:37:30,290 --> 00:37:32,520 What do you think? 882 00:37:32,520 --> 00:37:34,110 People who are blind read. 883 00:37:37,130 --> 00:37:37,880 What do you think? 884 00:37:37,880 --> 00:37:40,370 AUDIENCE: So the connection between here and the visual 885 00:37:40,370 --> 00:37:46,060 system for the blind people goes from that region and touching, 886 00:37:46,060 --> 00:37:46,820 since they're-- 887 00:37:46,820 --> 00:37:47,580 I don't know. 888 00:37:47,580 --> 00:37:48,890 NANCY KANWISHER: Yeah. 889 00:37:48,890 --> 00:37:50,180 Yeah, it's not obvious. 890 00:37:50,180 --> 00:37:51,170 It's not obvious. 891 00:37:51,170 --> 00:37:52,680 There are several papers-- 892 00:37:52,680 --> 00:37:53,840 which I was going to put in this lecture 893 00:37:53,840 --> 00:37:54,860 and I just couldn't fit. 894 00:37:54,860 --> 00:37:56,270 But there are several papers that 895 00:37:56,270 --> 00:38:00,500 argue that tactile Braille reading in congenitally 896 00:38:00,500 --> 00:38:04,430 blind people activates that same region. 897 00:38:04,430 --> 00:38:05,980 They're pretty good papers. 898 00:38:05,980 --> 00:38:07,220 I sort of believe it. 899 00:38:07,220 --> 00:38:09,830 I have-- as I say, I'm a little bit of a hard ass, 900 00:38:09,830 --> 00:38:12,860 so I'm not 100% convinced, but they're pretty compelling, 901 00:38:12,860 --> 00:38:16,410 and it's a very interesting question. 902 00:38:16,410 --> 00:38:17,787 And it's a whole saga. 903 00:38:17,787 --> 00:38:18,620 It's so interesting. 904 00:38:18,620 --> 00:38:19,700 I'm going to try to incorporate more 905 00:38:19,700 --> 00:38:21,825 of this in a later lecture, because I didn't fit it 906 00:38:21,825 --> 00:38:22,610 in here. 907 00:38:22,610 --> 00:38:24,080 Yeah. 908 00:38:24,080 --> 00:38:26,690 And the idea would be, if you had 909 00:38:26,690 --> 00:38:29,840 to guess, what will those connections be that drive that? 910 00:38:29,840 --> 00:38:31,220 Certainly not visual input. 911 00:38:31,220 --> 00:38:33,030 They're not getting visual input. 912 00:38:33,030 --> 00:38:35,300 So it would have to be input from language-y regions 913 00:38:35,300 --> 00:38:37,370 or something like that, that would also 914 00:38:37,370 --> 00:38:39,110 be present in blind people. 915 00:38:39,110 --> 00:38:41,340 See what I mean? 916 00:38:41,340 --> 00:38:42,740 OK. 917 00:38:42,740 --> 00:38:43,280 All right. 918 00:38:43,280 --> 00:38:46,730 Anyway, all of this just to say that it looks 919 00:38:46,730 --> 00:38:48,913 like the visual word form area is 920 00:38:48,913 --> 00:38:50,330 kind of special in the human brain 921 00:38:50,330 --> 00:38:53,120 because, one, it shows us that at least one region gets 922 00:38:53,120 --> 00:38:56,490 its selectivity from experience, and two, 923 00:38:56,490 --> 00:38:59,120 because it develops later, it gave us this opportunity 924 00:38:59,120 --> 00:39:02,480 to ask if the connectivity was present before the function 925 00:39:02,480 --> 00:39:08,120 as a sort of weak test of this hypothesis that connectivity 926 00:39:08,120 --> 00:39:08,990 determines function. 927 00:39:11,540 --> 00:39:12,380 All right. 928 00:39:12,380 --> 00:39:13,070 Boom. 929 00:39:13,070 --> 00:39:14,390 All right, so where are we? 930 00:39:14,390 --> 00:39:17,360 This really is a shaggy dog story lecture. 931 00:39:17,360 --> 00:39:17,870 OK. 932 00:39:17,870 --> 00:39:21,110 So we started off by saying a lot of the basic structure 933 00:39:21,110 --> 00:39:22,730 of the brain is innate. 934 00:39:22,730 --> 00:39:25,730 Most of the neurons in your brain, you had at birth. 935 00:39:25,730 --> 00:39:27,273 Most of the long-range connections 936 00:39:27,273 --> 00:39:28,190 were present at birth. 937 00:39:28,190 --> 00:39:31,550 They weren't yet myelinated, but they were there. 938 00:39:31,550 --> 00:39:34,760 We've argued that some of these selective cortical regions 939 00:39:34,760 --> 00:39:37,400 appear to depend on experience. 940 00:39:37,400 --> 00:39:39,080 For example, the face-deprived monkeys 941 00:39:39,080 --> 00:39:41,180 don't have face patches. 942 00:39:41,180 --> 00:39:45,380 And the ferrets see the response of an auditory cortex 943 00:39:45,380 --> 00:39:46,970 when their auditory cortex has been 944 00:39:46,970 --> 00:39:48,470 rewired to get visual input. 945 00:39:51,500 --> 00:39:54,050 And further, I've argued that the visual word form 946 00:39:54,050 --> 00:39:59,000 area, the selectivity of that region can't be innate, 947 00:39:59,000 --> 00:40:02,120 and yet it arises at a consistent location, 948 00:40:02,120 --> 00:40:04,310 possibly because of these long-range connections 949 00:40:04,310 --> 00:40:07,120 of that region. 950 00:40:07,120 --> 00:40:09,790 So all of this looks very experiential, 951 00:40:09,790 --> 00:40:12,860 aside from the structural stuff that's present at birth. 952 00:40:12,860 --> 00:40:15,790 So is Kant toast? 953 00:40:15,790 --> 00:40:17,680 I started last lecture as saying he 954 00:40:17,680 --> 00:40:20,830 was reacting against the empiricist, 955 00:40:20,830 --> 00:40:23,410 saying not everything is derived from experience. 956 00:40:23,410 --> 00:40:26,860 We need to have a priori conditions of cognition. 957 00:40:26,860 --> 00:40:29,440 Remember, he said, "space can be given 958 00:40:29,440 --> 00:40:34,390 prior to all actual perceptions, and so exist in the mind 959 00:40:34,390 --> 00:40:36,070 a priori. 960 00:40:36,070 --> 00:40:38,980 And it can contain, prior to all experience, principles 961 00:40:38,980 --> 00:40:42,100 which determine the relations of these objects." 962 00:40:42,100 --> 00:40:45,310 So he's basically saying we have an innate representation 963 00:40:45,310 --> 00:40:46,352 of space. 964 00:40:46,352 --> 00:40:48,310 And I've just been giving you all this evidence 965 00:40:48,310 --> 00:40:50,950 for all the other cases that experience seems 966 00:40:50,950 --> 00:40:53,390 to be playing the major role. 967 00:40:53,390 --> 00:40:57,100 So is it all over for Kant? 968 00:40:57,100 --> 00:41:00,802 Well, actually, Kant was talking about space and time primarily, 969 00:41:00,802 --> 00:41:02,260 and we haven't considered that yet. 970 00:41:02,260 --> 00:41:04,840 So let's get back to space. 971 00:41:04,840 --> 00:41:08,230 Remember these spatial representations 972 00:41:08,230 --> 00:41:10,510 that I talked about in the rodent brain. 973 00:41:10,510 --> 00:41:12,340 Four different kinds of neurons that 974 00:41:12,340 --> 00:41:15,550 are present in adult rodents that play wonderfully 975 00:41:15,550 --> 00:41:18,100 different roles in navigation. 976 00:41:18,100 --> 00:41:20,500 Remember, there are place cells that fire only 977 00:41:20,500 --> 00:41:23,560 when the rodent is in a given known place in his environment. 978 00:41:23,560 --> 00:41:25,810 There are direction cells that fire only 979 00:41:25,810 --> 00:41:27,670 when the rodent is oriented in a given 980 00:41:27,670 --> 00:41:29,290 direction in his environment. 981 00:41:29,290 --> 00:41:31,750 There are border cells that fire only 982 00:41:31,750 --> 00:41:34,695 when the rodent is near a border of the space he's in, 983 00:41:34,695 --> 00:41:36,070 like right now, I have cells that 984 00:41:36,070 --> 00:41:38,403 are firing because I'm next to this border of this space 985 00:41:38,403 --> 00:41:41,830 that I'm in, and Anna does not have any of those cells firing 986 00:41:41,830 --> 00:41:44,380 because she's in the middle of this space. 987 00:41:44,380 --> 00:41:46,930 And there are grid cells that have this amazing property 988 00:41:46,930 --> 00:41:50,800 of firing in a hexagonal array of little micro place 989 00:41:50,800 --> 00:41:54,820 cells spaced evenly in a hexagonal array. 990 00:41:54,820 --> 00:41:58,180 OK, so all of this apparatus that I talked about last time 991 00:41:58,180 --> 00:42:00,910 that seems to be playing a role in your concept of where you 992 00:42:00,910 --> 00:42:05,810 are, where you're oriented, and the space around you, 993 00:42:05,810 --> 00:42:08,033 if we had to take some representation of space 994 00:42:08,033 --> 00:42:09,700 that Kant might have been talking about, 995 00:42:09,700 --> 00:42:11,440 this would be it. 996 00:42:11,440 --> 00:42:13,900 So is this stuff innate? 997 00:42:13,900 --> 00:42:17,650 Well, happily, all this work was done originally in rodents. 998 00:42:17,650 --> 00:42:20,260 All the most detailed work was done in rodents, 999 00:42:20,260 --> 00:42:23,570 so we can ask that question, because it's an animal. 1000 00:42:23,570 --> 00:42:24,320 OK? 1001 00:42:24,320 --> 00:42:25,370 All right. 1002 00:42:25,370 --> 00:42:29,270 So what the Mosers and their colleagues-- 1003 00:42:29,270 --> 00:42:33,050 the husband-wife team who got the Nobel Prize in 2014 1004 00:42:33,050 --> 00:42:34,820 for their work on the grid cells-- 1005 00:42:34,820 --> 00:42:37,610 and O'Keefe and their colleagues in London, 1006 00:42:37,610 --> 00:42:39,680 who discovered place cells in the first place-- 1007 00:42:39,680 --> 00:42:42,470 two different groups simultaneously realized what 1008 00:42:42,470 --> 00:42:44,467 a huge, big, fabulous question this was, 1009 00:42:44,467 --> 00:42:46,550 and they both did the experiment at the same time, 1010 00:42:46,550 --> 00:42:50,210 and they published it together at the same time about four 1011 00:42:50,210 --> 00:42:51,200 years ago in-- 1012 00:42:51,200 --> 00:42:52,970 I forget-- Science or Nature. 1013 00:42:52,970 --> 00:42:54,500 Big event in the field. 1014 00:42:54,500 --> 00:42:57,020 So they both realize the same thing. 1015 00:42:57,020 --> 00:43:01,130 The way rodents grow up, they hang out in a dark nest. 1016 00:43:01,130 --> 00:43:05,720 They're very premature at birth, and they can't really do much. 1017 00:43:05,720 --> 00:43:06,890 They can't move around. 1018 00:43:06,890 --> 00:43:08,690 All they can do is turn their head 1019 00:43:08,690 --> 00:43:10,190 toward a nipple and suck milk. 1020 00:43:10,190 --> 00:43:12,470 That's kind of it. 1021 00:43:12,470 --> 00:43:14,660 And so there they are, in the nest, in the dark. 1022 00:43:14,660 --> 00:43:18,440 Their eyes don't even open until the end 1023 00:43:18,440 --> 00:43:19,910 of the second week of life. 1024 00:43:19,910 --> 00:43:22,055 And at the same time, it's the first time 1025 00:43:22,055 --> 00:43:23,930 they emerge from the nest, and the first time 1026 00:43:23,930 --> 00:43:27,440 they have any experience navigating, any real experience 1027 00:43:27,440 --> 00:43:29,750 of space. 1028 00:43:29,750 --> 00:43:32,000 And so we can ask which of those cells 1029 00:43:32,000 --> 00:43:35,570 are present, the very first experience. 1030 00:43:35,570 --> 00:43:37,400 And it turns out that-- 1031 00:43:37,400 --> 00:43:38,900 sorry, this is a little hard to see. 1032 00:43:38,900 --> 00:43:40,640 There's a light yellow overlay. 1033 00:43:40,640 --> 00:43:42,950 This is the window when they first open their eyes 1034 00:43:42,950 --> 00:43:45,560 and leave the nest, between postnatal day 1035 00:43:45,560 --> 00:43:49,160 12 and 14, the end of the second week of life. 1036 00:43:49,160 --> 00:43:51,290 And what you see is the head direction cells are 1037 00:43:51,290 --> 00:43:54,440 present immediately, as soon as the-- can first 1038 00:43:54,440 --> 00:43:59,120 collect neurophysiology data from these newborn rat pups. 1039 00:43:59,120 --> 00:44:01,560 They're there right away. 1040 00:44:01,560 --> 00:44:05,420 Place cells, you can get them pretty early, 1041 00:44:05,420 --> 00:44:10,700 and grid cells soon after that. 1042 00:44:10,700 --> 00:44:14,300 So this suggests that in the rodents, at least, 1043 00:44:14,300 --> 00:44:18,290 their representation of space as entailed 1044 00:44:18,290 --> 00:44:21,560 in the properties of these neurons is largely innate. 1045 00:44:25,860 --> 00:44:29,160 So just like Kant said way back in the 1700s. 1046 00:44:29,160 --> 00:44:30,030 Everybody get this? 1047 00:44:30,030 --> 00:44:31,760 It's pretty cool. 1048 00:44:31,760 --> 00:44:33,510 It's a rare opportunity where you can just 1049 00:44:33,510 --> 00:44:36,480 take a huge, big philosophical question 1050 00:44:36,480 --> 00:44:39,510 and, boom, answer it with data. 1051 00:44:39,510 --> 00:44:40,110 Yeah. 1052 00:44:40,110 --> 00:44:40,950 Awesome. 1053 00:44:40,950 --> 00:44:41,760 OK. 1054 00:44:41,760 --> 00:44:42,390 Yes. 1055 00:44:42,390 --> 00:44:43,040 AUDIENCE: Wait, sorry-- 1056 00:44:43,040 --> 00:44:43,980 NANCY KANWISHER: I'm sorry, is it Martin? 1057 00:44:43,980 --> 00:44:44,690 Yeah. 1058 00:44:44,690 --> 00:44:46,690 AUDIENCE: Sorry, are you saying that it's innate 1059 00:44:46,690 --> 00:44:47,760 or that it's learned? 1060 00:44:47,760 --> 00:44:48,760 NANCY KANWISHER: Innate. 1061 00:44:48,760 --> 00:44:49,260 Innate. 1062 00:44:49,260 --> 00:44:49,875 AUDIENCE: --takes time-- 1063 00:44:49,875 --> 00:44:51,630 NANCY KANWISHER: Because-- oh, yeah. 1064 00:44:51,630 --> 00:44:53,280 OK, important point. 1065 00:44:53,280 --> 00:44:55,980 OK, we don't know before then whether they existed. 1066 00:44:55,980 --> 00:44:56,970 They were in the nest. 1067 00:44:56,970 --> 00:44:59,460 You can't really do neurophysiology 1068 00:44:59,460 --> 00:45:01,020 on the rodents in the nest. 1069 00:45:01,020 --> 00:45:03,000 The point is, none of the relevant experience 1070 00:45:03,000 --> 00:45:04,320 has happened before then. 1071 00:45:04,320 --> 00:45:06,810 They haven't opened their eyes, they haven't navigated. 1072 00:45:06,810 --> 00:45:08,550 So none of the experience that could 1073 00:45:08,550 --> 00:45:12,690 be relevant for navigation has happened before right here, 1074 00:45:12,690 --> 00:45:15,840 on the very first time that you can test it, 1075 00:45:15,840 --> 00:45:19,140 and the very first time that they could possibly 1076 00:45:19,140 --> 00:45:21,150 be in the world, seeing the world, navigating, 1077 00:45:21,150 --> 00:45:22,600 they have them. 1078 00:45:22,600 --> 00:45:24,630 But what you point to is an important point. 1079 00:45:24,630 --> 00:45:26,088 I mentioned this briefly last time, 1080 00:45:26,088 --> 00:45:28,447 but it's really worth repeating. 1081 00:45:28,447 --> 00:45:30,030 Innate-- I guess the word "innate" can 1082 00:45:30,030 --> 00:45:32,790 be used different ways, but what I mean by innate here, 1083 00:45:32,790 --> 00:45:36,330 the relevant part of innate, the content to the big questions, 1084 00:45:36,330 --> 00:45:39,540 is whether it's specified at birth, not 1085 00:45:39,540 --> 00:45:41,640 whether it exists at birth. 1086 00:45:41,640 --> 00:45:44,370 Remember, I gave the case of puberty. 1087 00:45:44,370 --> 00:45:47,100 Puberty happens way after birth, but it's not 1088 00:45:47,100 --> 00:45:48,270 the result of experience. 1089 00:45:48,270 --> 00:45:49,770 It's part of a genetic program. 1090 00:45:49,770 --> 00:45:52,170 It's just going to happen. 1091 00:45:52,170 --> 00:45:54,420 I mean, I guess if you don't eat anything, you'll die 1092 00:45:54,420 --> 00:45:57,090 and then it won't happen, but within broad latitude, 1093 00:45:57,090 --> 00:45:59,070 it's not the result of experience. 1094 00:45:59,070 --> 00:46:03,690 And so you can have maturation on a biological autopilot that 1095 00:46:03,690 --> 00:46:05,700 continues independent of experience, 1096 00:46:05,700 --> 00:46:07,590 and that's the relevant kind of innate. 1097 00:46:07,590 --> 00:46:10,190 I realize I was probably confusing. 1098 00:46:10,190 --> 00:46:13,060 Innate for this purpose doesn't mean present at birth. 1099 00:46:13,060 --> 00:46:16,050 It means determined at birth, essentially, 1100 00:46:16,050 --> 00:46:18,980 independent of experience. 1101 00:46:18,980 --> 00:46:19,843 Good. 1102 00:46:19,843 --> 00:46:21,260 You guys are asking good questions 1103 00:46:21,260 --> 00:46:23,300 and it's helping me be clearer. 1104 00:46:23,300 --> 00:46:24,560 OK. 1105 00:46:24,560 --> 00:46:26,540 OK, so that's cool. 1106 00:46:26,540 --> 00:46:29,060 That says that those cells are all 1107 00:46:29,060 --> 00:46:32,000 present very early on, and presumably independent 1108 00:46:32,000 --> 00:46:33,620 of experience. 1109 00:46:33,620 --> 00:46:35,600 What about re-orientation? 1110 00:46:35,600 --> 00:46:38,180 Remember, re-orientation is this cool thing 1111 00:46:38,180 --> 00:46:39,863 that I carried on for a long time about 1112 00:46:39,863 --> 00:46:41,030 because it's so interesting. 1113 00:46:41,030 --> 00:46:43,820 Reorientation is this particular aspect 1114 00:46:43,820 --> 00:46:45,140 of the navigation system. 1115 00:46:45,140 --> 00:46:48,680 It's been studied behaviorally in rodents, in young humans, 1116 00:46:48,680 --> 00:46:50,480 and human adults. 1117 00:46:50,480 --> 00:46:52,190 And lots of other animals, actually. 1118 00:46:52,190 --> 00:46:54,620 And the key thing about reorientation 1119 00:46:54,620 --> 00:46:57,560 is this is how an animal gets their bearing when 1120 00:46:57,560 --> 00:46:58,760 they're disoriented. 1121 00:46:58,760 --> 00:47:02,630 And the key finding is they use the shape of space around them. 1122 00:47:02,630 --> 00:47:06,690 They don't use landmarks to reorient themselves. 1123 00:47:06,690 --> 00:47:07,670 That's the key finding. 1124 00:47:07,670 --> 00:47:09,630 This is all stuff I talked about before. 1125 00:47:09,630 --> 00:47:13,310 And the evidence that animals use the shape of space 1126 00:47:13,310 --> 00:47:18,170 to reorient is, when you have shown a rodent that there's 1127 00:47:18,170 --> 00:47:22,670 goodies in that corner, the left side of the short wall, 1128 00:47:22,670 --> 00:47:25,520 essentially, and then you disorient him and put him back 1129 00:47:25,520 --> 00:47:28,430 in the box, he goes 50/50 to those two corners, 1130 00:47:28,430 --> 00:47:29,900 showing that he's learned something 1131 00:47:29,900 --> 00:47:33,080 like the food is on the left side of the short wall. 1132 00:47:33,080 --> 00:47:36,020 Not in words, presumably, but some mental language 1133 00:47:36,020 --> 00:47:38,870 that holds that information. 1134 00:47:38,870 --> 00:47:44,210 OK, so that's using the shape of space for reorientation. 1135 00:47:44,210 --> 00:47:46,963 Is that ability to use the shape of space-- 1136 00:47:46,963 --> 00:47:48,380 this is a different sense of space 1137 00:47:48,380 --> 00:47:50,930 than head direction cells, the shape of space around you-- 1138 00:47:50,930 --> 00:47:55,580 is that present independent of experience? 1139 00:47:55,580 --> 00:47:58,940 Well, again, we can't test that in humans 1140 00:47:58,940 --> 00:48:01,488 because we can't deprive humans of experiencing 1141 00:48:01,488 --> 00:48:02,780 the shape of space around them. 1142 00:48:02,780 --> 00:48:03,890 Was there a question? 1143 00:48:03,890 --> 00:48:04,390 No? 1144 00:48:04,390 --> 00:48:06,650 OK, all right. 1145 00:48:06,650 --> 00:48:11,230 But we can test it in animals with something 1146 00:48:11,230 --> 00:48:14,540 called controlled rearing that I've talked about before. 1147 00:48:14,540 --> 00:48:18,490 So again, we can't test this-- even in animals, 1148 00:48:18,490 --> 00:48:19,960 it's hard to test at birth. 1149 00:48:19,960 --> 00:48:23,380 Lots of animals can't navigate very well at birth, right? 1150 00:48:23,380 --> 00:48:25,708 So we want to test them after birth, 1151 00:48:25,708 --> 00:48:28,000 but we don't want them to have the relevant experience, 1152 00:48:28,000 --> 00:48:29,050 because that's what we're asking, 1153 00:48:29,050 --> 00:48:30,640 is would this ability be there even 1154 00:48:30,640 --> 00:48:33,340 without the relevant experience. 1155 00:48:33,340 --> 00:48:34,000 OK. 1156 00:48:34,000 --> 00:48:38,470 So the answer to all of this, the way around this 1157 00:48:38,470 --> 00:48:40,480 is to use controlled rearing. 1158 00:48:40,480 --> 00:48:44,050 Just like Sugita did with the face-deprived monkeys, 1159 00:48:44,050 --> 00:48:47,170 and just like our Carl also did with face-deprived monkeys-- 1160 00:48:47,170 --> 00:48:50,890 the behavioral study and the functional MRI study. 1161 00:48:50,890 --> 00:48:54,070 But this will be a controlled rearing 1162 00:48:54,070 --> 00:48:56,830 study in a different organism, and it's pretty cute. 1163 00:48:56,830 --> 00:48:57,805 It goes like this. 1164 00:48:57,805 --> 00:48:59,530 This is a group in Italy that has 1165 00:48:59,530 --> 00:49:01,300 a whole lab that uses this paradigm, 1166 00:49:01,300 --> 00:49:03,530 and it's very, very powerful. 1167 00:49:03,530 --> 00:49:07,630 So what they do is they-- 1168 00:49:07,630 --> 00:49:08,650 again, I just said this. 1169 00:49:08,650 --> 00:49:09,820 The whole idea is raise an animal 1170 00:49:09,820 --> 00:49:11,650 without the relevant experience, figure out 1171 00:49:11,650 --> 00:49:13,870 if the ability arises anyway. 1172 00:49:13,870 --> 00:49:17,950 So in this case, what they do is they 1173 00:49:17,950 --> 00:49:21,670 get fertilized eggs, chicken eggs from a local hatchery 1174 00:49:21,670 --> 00:49:24,730 that's conveniently near their lab. 1175 00:49:24,730 --> 00:49:27,460 They bring those fertilized eggs into the lab 1176 00:49:27,460 --> 00:49:30,790 and put them in an incubator, and they hatch them 1177 00:49:30,790 --> 00:49:31,375 in darkness. 1178 00:49:34,020 --> 00:49:36,643 Then for the first few days, you get a nice little chicken. 1179 00:49:36,643 --> 00:49:39,060 It's in the light here, but that's just so you can see it. 1180 00:49:39,060 --> 00:49:40,990 It actually hatches in the darkness, 1181 00:49:40,990 --> 00:49:43,860 so there's no visual experience. 1182 00:49:43,860 --> 00:49:48,810 Then you put them in cages of different shapes. 1183 00:49:48,810 --> 00:49:51,570 Either a nice rectangular shape like this 1184 00:49:51,570 --> 00:49:53,880 that would be relevant for reorienting, 1185 00:49:53,880 --> 00:49:57,900 or a circular space like that that has no geometric cues 1186 00:49:57,900 --> 00:50:00,660 because it's symmetrical. 1187 00:50:00,660 --> 00:50:03,420 So they spend their first three days of life in one 1188 00:50:03,420 --> 00:50:05,820 or the other of those containers. 1189 00:50:08,640 --> 00:50:11,920 You then, in order to get a behavioral result out of them, 1190 00:50:11,920 --> 00:50:13,920 you have to use their natural behavior, which is 1191 00:50:13,920 --> 00:50:16,710 that they imprint on mama bird. 1192 00:50:16,710 --> 00:50:20,280 And you may know that imprinting is pretty non-specific. 1193 00:50:20,280 --> 00:50:23,970 Baby birds will imprint on nearly anything that moves. 1194 00:50:23,970 --> 00:50:26,190 So they take a big, red plastic object, 1195 00:50:26,190 --> 00:50:28,200 and they dangle it in the middle of the cage, 1196 00:50:28,200 --> 00:50:30,000 and little chicks follow the red object. 1197 00:50:30,000 --> 00:50:31,050 That's mom. 1198 00:50:31,050 --> 00:50:34,270 That's what they do. 1199 00:50:34,270 --> 00:50:40,290 So then you can use that behavior to test their ability. 1200 00:50:40,290 --> 00:50:43,020 And so you get them in the groove. 1201 00:50:43,020 --> 00:50:48,780 You show them mom, and mom disappears behind an occluder. 1202 00:50:48,780 --> 00:50:52,410 And then you let the chick go follow mom, 1203 00:50:52,410 --> 00:50:53,760 which the chick wants to do. 1204 00:50:53,760 --> 00:50:55,320 So they do a few trials like that. 1205 00:50:55,320 --> 00:50:56,070 They've imprinted. 1206 00:50:56,070 --> 00:50:57,237 They're going to follow mom. 1207 00:50:57,237 --> 00:50:59,190 This gives us a way to ask the chick, 1208 00:50:59,190 --> 00:51:00,750 where do you think mom is? 1209 00:51:00,750 --> 00:51:02,970 And that gives us a way to ask, what 1210 00:51:02,970 --> 00:51:06,090 cues are you using to reorient, even though you've been raised 1211 00:51:06,090 --> 00:51:09,390 without geometric information. 1212 00:51:09,390 --> 00:51:10,200 All right. 1213 00:51:10,200 --> 00:51:12,372 And the thing I really love about this-- 1214 00:51:12,372 --> 00:51:13,830 oh, I guess it's on a later slide-- 1215 00:51:13,830 --> 00:51:15,820 is that after you do the whole experiment, 1216 00:51:15,820 --> 00:51:17,730 you take one or two trials on that chick, 1217 00:51:17,730 --> 00:51:18,870 you're done with that chick, they 1218 00:51:18,870 --> 00:51:20,550 have the relevant experience, you give them 1219 00:51:20,550 --> 00:51:22,842 back to the hatchery and the hatchery does their thing. 1220 00:51:22,842 --> 00:51:25,890 So it's just like a really nice little symbiotic 1221 00:51:25,890 --> 00:51:29,700 science-farming enterprise. 1222 00:51:29,700 --> 00:51:32,070 OK, so here's actually what they do. 1223 00:51:32,070 --> 00:51:35,610 So here's how the re-orientation test goes. 1224 00:51:35,610 --> 00:51:39,270 After this chick is raised in one of those two environments-- 1225 00:51:39,270 --> 00:51:42,090 the circular one with no geometric information, 1226 00:51:42,090 --> 00:51:45,450 or the rectangular one with geometric information-- 1227 00:51:45,450 --> 00:51:49,980 and they've learned to follow big red plastic mom, 1228 00:51:49,980 --> 00:51:53,640 you then put the chick in this box here. 1229 00:51:53,640 --> 00:51:55,740 The chick is in there in this wire mesh 1230 00:51:55,740 --> 00:51:58,150 that holds them in there so he can't run around. 1231 00:51:58,150 --> 00:51:59,940 He's in this rectangular space, and there 1232 00:51:59,940 --> 00:52:05,520 are four symmetrical occluders in the corner. 1233 00:52:05,520 --> 00:52:07,860 You then take the red object-- 1234 00:52:07,860 --> 00:52:10,860 mom-- and hide it behind one of the blue panels 1235 00:52:10,860 --> 00:52:13,770 in full view of the chick. 1236 00:52:13,770 --> 00:52:16,290 So now the chick knows where mom is. 1237 00:52:16,290 --> 00:52:20,460 Now you bring down an opaque cylinder 1238 00:52:20,460 --> 00:52:21,960 around where the chick is. 1239 00:52:25,460 --> 00:52:27,620 And while the opaque cylinder is down, 1240 00:52:27,620 --> 00:52:30,840 you rotate the box 90 degrees. 1241 00:52:30,840 --> 00:52:35,000 So now, the chick has no way to tell things are rotated, 1242 00:52:35,000 --> 00:52:39,650 I'm disoriented, what's what, how do I know where to go. 1243 00:52:39,650 --> 00:52:43,310 So this is reorientation in a newly-hatched chick that's 1244 00:52:43,310 --> 00:52:47,070 been reared under controlled conditions. 1245 00:52:47,070 --> 00:52:47,570 All right. 1246 00:52:47,570 --> 00:52:51,110 So now, once you rotate the box, then you 1247 00:52:51,110 --> 00:52:54,980 lift up the opaque occluder, and the cage, 1248 00:52:54,980 --> 00:52:57,038 and you see where the chick goes. 1249 00:52:57,038 --> 00:52:57,830 Everybody get this? 1250 00:52:57,830 --> 00:52:59,038 It's a little bit convoluted. 1251 00:52:59,038 --> 00:53:00,590 But it's just a version-- 1252 00:53:00,590 --> 00:53:02,982 it's a chick version of the same reorientation task we've 1253 00:53:02,982 --> 00:53:04,190 been talking about all along. 1254 00:53:08,360 --> 00:53:11,600 You do 16 trials, and then you give the chick back 1255 00:53:11,600 --> 00:53:13,100 to the hatchery. 1256 00:53:13,100 --> 00:53:13,610 OK. 1257 00:53:13,610 --> 00:53:17,300 So here's what happens for chicks that are raised 1258 00:53:17,300 --> 00:53:18,890 in that rectangular cage. 1259 00:53:18,890 --> 00:53:21,560 They have geometric experience during those first three 1260 00:53:21,560 --> 00:53:23,090 days of life. 1261 00:53:23,090 --> 00:53:24,920 So this is kind of a control case. 1262 00:53:24,920 --> 00:53:27,980 And what you find is that when you've 1263 00:53:27,980 --> 00:53:31,190 hid mom in a corner that is on the right side 1264 00:53:31,190 --> 00:53:33,800 of the short wall, they go preferentially 1265 00:53:33,800 --> 00:53:36,260 to the two corners consistent with that more 1266 00:53:36,260 --> 00:53:39,620 than the other two corners, consistent with the idea 1267 00:53:39,620 --> 00:53:41,960 that they can use geometric information to reorient 1268 00:53:41,960 --> 00:53:42,890 themselves. 1269 00:53:42,890 --> 00:53:46,305 They're not perfect, but they're way better than chance. 1270 00:53:46,305 --> 00:53:47,180 Does that make sense? 1271 00:53:47,180 --> 00:53:49,650 They go to the two corners that are consistent, 1272 00:53:49,650 --> 00:53:51,930 showing that they can use the geometric information. 1273 00:53:51,930 --> 00:53:53,638 But these are the chicks that were raised 1274 00:53:53,638 --> 00:53:55,520 with the geometric experience. 1275 00:53:55,520 --> 00:53:57,530 What about the chicks raised in the cylinder, 1276 00:53:57,530 --> 00:54:01,550 without geometric experience? 1277 00:54:01,550 --> 00:54:04,620 They do the same thing. 1278 00:54:04,620 --> 00:54:06,620 And this is the first time they've experienced-- 1279 00:54:06,620 --> 00:54:10,010 this testing condition is the first time they've experienced 1280 00:54:10,010 --> 00:54:12,950 any space that isn't symmetrical, 1281 00:54:12,950 --> 00:54:14,930 any place where they could possibly 1282 00:54:14,930 --> 00:54:17,090 use geometric information to orient, 1283 00:54:17,090 --> 00:54:18,785 and they do it on the first trials. 1284 00:54:21,780 --> 00:54:23,700 Everybody got that? 1285 00:54:23,700 --> 00:54:26,070 So that tells us that this ability 1286 00:54:26,070 --> 00:54:29,550 to reorient based on the shape of space 1287 00:54:29,550 --> 00:54:34,530 when you're disoriented doesn't require experience 1288 00:54:34,530 --> 00:54:38,650 with the geometry of space. 1289 00:54:38,650 --> 00:54:42,970 Now, you might be thinking, well, that cylindrical cage, 1290 00:54:42,970 --> 00:54:46,277 it doesn't have something to break the symmetry, 1291 00:54:46,277 --> 00:54:47,860 but there's still something geometric. 1292 00:54:47,860 --> 00:54:49,450 There's a floor, there's a wall. 1293 00:54:49,450 --> 00:54:51,250 I agree, that bugged me too. 1294 00:54:51,250 --> 00:54:54,100 They did another experiment in which they raised the chicks 1295 00:54:54,100 --> 00:54:55,420 in total darkness. 1296 00:54:55,420 --> 00:54:59,110 First three days, no visual experience at all, 1297 00:54:59,110 --> 00:55:01,300 and the chicks still do that. 1298 00:55:01,300 --> 00:55:03,460 So no visual experience. 1299 00:55:03,460 --> 00:55:04,962 That's an even stronger case. 1300 00:55:04,962 --> 00:55:06,670 Was there a question percolating in here? 1301 00:55:06,670 --> 00:55:09,610 I felt like-- no, OK. 1302 00:55:09,610 --> 00:55:10,450 All right. 1303 00:55:10,450 --> 00:55:13,300 So yes, the reorientation system-- actually, 1304 00:55:13,300 --> 00:55:14,650 that's not well expressed. 1305 00:55:14,650 --> 00:55:18,070 The ability to use geometry to reorient 1306 00:55:18,070 --> 00:55:20,620 is not based on any experience with geometry. 1307 00:55:20,620 --> 00:55:24,130 It must be innate in the sense of not requiring experience. 1308 00:55:29,870 --> 00:55:30,585 So go Kant. 1309 00:55:33,870 --> 00:55:35,070 All right. 1310 00:55:35,070 --> 00:55:36,450 So where have we gotten to? 1311 00:55:36,450 --> 00:55:38,670 Let's recap. 1312 00:55:38,670 --> 00:55:39,810 What's innate? 1313 00:55:39,810 --> 00:55:41,040 OK, in the face system-- 1314 00:55:41,040 --> 00:55:43,500 I went through this before, maybe not that much. 1315 00:55:43,500 --> 00:55:46,800 We could quibble some of the cases are ambiguous, 1316 00:55:46,800 --> 00:55:50,814 but the main evidence suggests that-- 1317 00:55:50,814 --> 00:55:52,770 before you posit that something's innate, 1318 00:55:52,770 --> 00:55:54,210 it's like the evidence-- you have 1319 00:55:54,210 --> 00:55:56,418 to have strong evidence for innateness to argue with. 1320 00:55:56,418 --> 00:55:58,440 The default case is not innate, right? 1321 00:55:58,440 --> 00:56:01,530 It's kind of an extreme claim, and so the default 1322 00:56:01,530 --> 00:56:04,890 is not innate, and so right now, we don't have a strong argument 1323 00:56:04,890 --> 00:56:07,680 that any of the face system is innate other than this bias 1324 00:56:07,680 --> 00:56:10,080 to look more at faces, which as I said 1325 00:56:10,080 --> 00:56:12,420 might be a very rudimentary template. 1326 00:56:12,420 --> 00:56:14,003 OK. 1327 00:56:14,003 --> 00:56:16,170 I talked about the role of connectivity and cortical 1328 00:56:16,170 --> 00:56:16,980 development. 1329 00:56:16,980 --> 00:56:19,290 Most of those long-range connections 1330 00:56:19,290 --> 00:56:21,180 are present at birth. 1331 00:56:21,180 --> 00:56:24,990 I showed that connectivity can causally affect development 1332 00:56:24,990 --> 00:56:28,170 in the case of the rewired ferrets. 1333 00:56:28,170 --> 00:56:31,140 I showed that category selective regions in human adults 1334 00:56:31,140 --> 00:56:33,420 have distinctive connectivity. 1335 00:56:33,420 --> 00:56:35,910 And I showed that in the visual word form area, 1336 00:56:35,910 --> 00:56:40,830 the distinctive connectivity is present before the function. 1337 00:56:40,830 --> 00:56:41,370 OK. 1338 00:56:41,370 --> 00:56:44,790 So that tells us that there's one region in the brain 1339 00:56:44,790 --> 00:56:49,140 that we know the selectivity of that region can't be innate. 1340 00:56:49,140 --> 00:56:51,060 It doesn't tell us about all the others. 1341 00:56:51,060 --> 00:56:52,097 Who knows? 1342 00:56:52,097 --> 00:56:53,430 It's kind of an existence proof. 1343 00:56:53,430 --> 00:56:55,360 They might all be learned by experience. 1344 00:56:55,360 --> 00:56:56,420 We look at faces a lot. 1345 00:56:56,420 --> 00:56:57,420 We look at scenes a lot. 1346 00:56:57,420 --> 00:56:58,620 We look at bodies a lot. 1347 00:56:58,620 --> 00:57:01,770 Maybe they all have the same experiential basis. 1348 00:57:01,770 --> 00:57:02,910 Doesn't prove it. 1349 00:57:02,910 --> 00:57:05,610 It just says maybe. 1350 00:57:05,610 --> 00:57:06,960 All right. 1351 00:57:06,960 --> 00:57:10,110 But then I showed that for the space system, actually, 1352 00:57:10,110 --> 00:57:14,310 we do have pretty strong evidence that a lot of it 1353 00:57:14,310 --> 00:57:16,590 is innate, both in that the head direction 1354 00:57:16,590 --> 00:57:20,710 cells are present before any visual experience 1355 00:57:20,710 --> 00:57:22,800 or any navigation. 1356 00:57:22,800 --> 00:57:25,080 And I showed that the chicks can reorient 1357 00:57:25,080 --> 00:57:27,450 based on the geometry of space, even if they've never 1358 00:57:27,450 --> 00:57:31,800 seen space or geometry before. 1359 00:57:31,800 --> 00:57:35,130 So bottom line, face system, who knows, 1360 00:57:35,130 --> 00:57:38,010 but no strong evidence for innateness. 1361 00:57:38,010 --> 00:57:40,290 Visual word form area, strong evidence 1362 00:57:40,290 --> 00:57:42,420 that it's experientially based, and space 1363 00:57:42,420 --> 00:57:45,240 system, strong evidence that a lot of it is innate. 1364 00:57:48,210 --> 00:57:50,460 OK. 1365 00:57:50,460 --> 00:57:51,240 All right. 1366 00:57:51,240 --> 00:57:52,230 I got us to here. 1367 00:57:52,230 --> 00:57:52,770 All right. 1368 00:57:52,770 --> 00:57:55,620 Now, all of this time, I've been talking about, 1369 00:57:55,620 --> 00:58:01,740 how do we wire up this system and its cognitive correlates 1370 00:58:01,740 --> 00:58:02,520 in development? 1371 00:58:02,520 --> 00:58:05,070 What do you have to build in to get a system like this 1372 00:58:05,070 --> 00:58:06,300 in development? 1373 00:58:06,300 --> 00:58:08,190 What can you get through learning? 1374 00:58:08,190 --> 00:58:12,100 What do you have to build in, and so forth. 1375 00:58:12,100 --> 00:58:16,470 But it's a related but different question to ask, 1376 00:58:16,470 --> 00:58:19,890 is that the only possible way it could work, 1377 00:58:19,890 --> 00:58:21,540 or are there situations where we might 1378 00:58:21,540 --> 00:58:25,050 have a very different kind of organization of the brain? 1379 00:58:25,050 --> 00:58:27,210 Are there other possible organizations 1380 00:58:27,210 --> 00:58:30,570 that might develop under different circumstances that 1381 00:58:30,570 --> 00:58:32,500 would still work? 1382 00:58:32,500 --> 00:58:35,190 And the two relevant cases that people have looked at 1383 00:58:35,190 --> 00:58:37,440 are cases of brain damage. 1384 00:58:37,440 --> 00:58:40,410 So if you have brain damage in adulthood, 1385 00:58:40,410 --> 00:58:42,780 and you lose a little piece, can that piece 1386 00:58:42,780 --> 00:58:44,250 move over and reorganize? 1387 00:58:44,250 --> 00:58:47,190 Is there another possible organization that would work? 1388 00:58:50,610 --> 00:58:52,590 Or what about if you have very, very 1389 00:58:52,590 --> 00:58:57,540 different visual experience, like you're born blind. 1390 00:58:57,540 --> 00:58:59,250 Then do you get the same organization, 1391 00:58:59,250 --> 00:59:01,500 or does everything go haywire and you have 1392 00:59:01,500 --> 00:59:05,610 a totally different kind of brain organization? 1393 00:59:05,610 --> 00:59:08,190 All right, so I'll give you a little bit of data 1394 00:59:08,190 --> 00:59:10,420 on each of those questions. 1395 00:59:10,420 --> 00:59:11,340 All right. 1396 00:59:11,340 --> 00:59:16,350 So first of all, can the brain reorganize after brain damage? 1397 00:59:16,350 --> 00:59:18,670 The main domain where people have studied this-- 1398 00:59:18,670 --> 00:59:22,050 which we haven't talked about yet, but we will in a month-- 1399 00:59:22,050 --> 00:59:23,640 is the case of language. 1400 00:59:23,640 --> 00:59:26,130 So it's just something there are lots of studies of this. 1401 00:59:26,130 --> 00:59:28,297 People have been onto this question for a long time. 1402 00:59:28,297 --> 00:59:32,550 In fact, Broca wrote about this question 200 years ago. 1403 00:59:32,550 --> 00:59:36,870 So the basic findings are that if you have damage 1404 00:59:36,870 --> 00:59:40,110 to your language parts of your brain in adulthood, 1405 00:59:40,110 --> 00:59:42,570 that is not good. 1406 00:59:42,570 --> 00:59:45,120 Often, you'll recover a little bit of function, 1407 00:59:45,120 --> 00:59:48,730 but you really won't get it back. 1408 00:59:48,730 --> 00:59:50,913 It's just a big massive drag. 1409 00:59:50,913 --> 00:59:52,830 There are people we will talk about in a month 1410 00:59:52,830 --> 00:59:56,670 when we get to the language section who 1411 00:59:56,670 --> 00:59:59,940 have had massive left hemisphere strokes that basically take out 1412 00:59:59,940 --> 01:00:03,060 their entire language system. 1413 01:00:03,060 --> 01:00:06,840 And it doesn't come back years after that stroke. 1414 01:00:06,840 --> 01:00:09,600 We'll see, actually, that they're cognitively pretty 1415 01:00:09,600 --> 01:00:10,860 normal in every other respect. 1416 01:00:10,860 --> 01:00:13,650 It's quite amazing how much they can do without language, 1417 01:00:13,650 --> 01:00:14,940 which is fascinating. 1418 01:00:14,940 --> 01:00:16,950 But for present purposes, the main finding 1419 01:00:16,950 --> 01:00:21,450 is brain damage in adulthood that takes out 1420 01:00:21,450 --> 01:00:23,880 language functions, not good. 1421 01:00:23,880 --> 01:00:26,370 Not much recovery, not much reorganization. 1422 01:00:26,370 --> 01:00:27,990 By the way, there's a whole-- it's 1423 01:00:27,990 --> 01:00:30,720 very trendy in popular media to talk about, oh, the brain is 1424 01:00:30,720 --> 01:00:32,730 plastic, you can rewire your brain, 1425 01:00:32,730 --> 01:00:36,090 take this-- use this smartphone app and rewire your brain. 1426 01:00:36,090 --> 01:00:39,267 Mostly, that stuff is just bullshit. 1427 01:00:39,267 --> 01:00:41,100 You can learn a task, and you can get better 1428 01:00:41,100 --> 01:00:43,050 at that task, no question. 1429 01:00:43,050 --> 01:00:45,420 But you can't make yourself smarter. 1430 01:00:45,420 --> 01:00:47,670 You can't rewire your whole brain. 1431 01:00:47,670 --> 01:00:50,400 That's garbage. 1432 01:00:50,400 --> 01:00:51,270 All right. 1433 01:00:51,270 --> 01:00:53,850 Back to aphasia. 1434 01:00:53,850 --> 01:00:55,050 OK. 1435 01:00:55,050 --> 01:00:59,040 The story is very different for brain damage in kids. 1436 01:00:59,040 --> 01:01:04,410 If you have brain damage in the first few months of life 1437 01:01:04,410 --> 01:01:07,780 to language parts of the brain, as an adult, 1438 01:01:07,780 --> 01:01:10,020 your language function is pretty good. 1439 01:01:10,020 --> 01:01:11,490 It's not quite perfect. 1440 01:01:11,490 --> 01:01:14,190 Took people a while to discover that it isn't quite perfect, 1441 01:01:14,190 --> 01:01:15,870 but it's surprisingly good. 1442 01:01:15,870 --> 01:01:18,620 For everyday uses, you might not even notice. 1443 01:01:18,620 --> 01:01:21,570 You have to test people on esoteric syntactic things 1444 01:01:21,570 --> 01:01:23,850 to discover that, actually, it's not quite right. 1445 01:01:23,850 --> 01:01:25,440 But it's very good. 1446 01:01:25,440 --> 01:01:28,770 And typically, what you see, if you scan these kids, 1447 01:01:28,770 --> 01:01:30,300 is that a lot of language function 1448 01:01:30,300 --> 01:01:33,450 has reorganized and shifted over to homologous regions 1449 01:01:33,450 --> 01:01:34,665 in the right hemisphere. 1450 01:01:37,440 --> 01:01:40,080 OK, so that's better news. 1451 01:01:40,080 --> 01:01:44,520 After age five, if you have brain damage, not so good. 1452 01:01:44,520 --> 01:01:47,340 So it's like there's some critical period 1453 01:01:47,340 --> 01:01:48,850 for when the brain is plastic. 1454 01:01:48,850 --> 01:01:51,300 You can move language over to the right hemisphere up 1455 01:01:51,300 --> 01:01:53,895 until around age five, and after that, you can't really. 1456 01:01:56,860 --> 01:01:59,740 All right, so these consider-- right, that's what I just said. 1457 01:01:59,740 --> 01:02:03,670 So these considerations have been pulled together 1458 01:02:03,670 --> 01:02:06,820 under something called the Kennard Principle. 1459 01:02:06,820 --> 01:02:08,620 And the Kennard Principle basically 1460 01:02:08,620 --> 01:02:11,215 says, if you're going to have brain damage, have it early. 1461 01:02:14,040 --> 01:02:15,610 Better not to have the brain damage, 1462 01:02:15,610 --> 01:02:18,510 but if you have to have it, have it early. 1463 01:02:18,510 --> 01:02:20,550 And that's based on findings like this-- 1464 01:02:20,550 --> 01:02:24,300 the fact that the kids who have left hemisphere damage 1465 01:02:24,300 --> 01:02:25,920 have much better language function 1466 01:02:25,920 --> 01:02:29,280 as adults than adults who have the same kind 1467 01:02:29,280 --> 01:02:31,410 of left hemisphere damage. 1468 01:02:31,410 --> 01:02:34,080 OK, so that's a reasonable summary 1469 01:02:34,080 --> 01:02:35,970 of the language literature. 1470 01:02:35,970 --> 01:02:41,070 However, this finding doesn't always hold. 1471 01:02:41,070 --> 01:02:45,990 And it has led others to put forth the Hebb Principle, which 1472 01:02:45,990 --> 01:02:48,150 is sort of the opposite. 1473 01:02:48,150 --> 01:02:51,190 The idea of the Hebb Principle is that, first of all, 1474 01:02:51,190 --> 01:02:52,150 it depends. 1475 01:02:52,150 --> 01:02:54,390 It depends on where the damage is. 1476 01:02:54,390 --> 01:02:58,770 It depends on when you test after brain damage. 1477 01:02:58,770 --> 01:03:02,277 But the key insight that will make this seem more sensible-- 1478 01:03:02,277 --> 01:03:04,110 at first, you feel like it's very intuitive. 1479 01:03:04,110 --> 01:03:07,230 Kids are more plastic in all kinds of ways, right? 1480 01:03:07,230 --> 01:03:10,680 Watch me using a computer, it drives my students insane, 1481 01:03:10,680 --> 01:03:11,490 I'm so slow. 1482 01:03:11,490 --> 01:03:13,290 One of my students once-- 1483 01:03:13,290 --> 01:03:15,120 back when I used to actually scan subjects, 1484 01:03:15,120 --> 01:03:17,103 one of my students was watching me scan, 1485 01:03:17,103 --> 01:03:19,020 and he's just getting more and more impatient, 1486 01:03:19,020 --> 01:03:23,070 and he finally is like, it's like watching my mother. 1487 01:03:23,070 --> 01:03:26,400 It's just like, you cannot become as fluent at things when 1488 01:03:26,400 --> 01:03:27,895 you start doing it when you're 50. 1489 01:03:27,895 --> 01:03:28,770 It's just what it is. 1490 01:03:28,770 --> 01:03:31,290 We've all seen that manifest in various ways. 1491 01:03:31,290 --> 01:03:33,930 OK, so that's generally true, and that's 1492 01:03:33,930 --> 01:03:35,730 consistent with this Kennard principles 1493 01:03:35,730 --> 01:03:39,383 that you have more flexibility when you're younger than older, 1494 01:03:39,383 --> 01:03:41,550 which is also why you guys should learn lots of math 1495 01:03:41,550 --> 01:03:43,770 and computer science now while your brains are still 1496 01:03:43,770 --> 01:03:44,550 good at it. 1497 01:03:44,550 --> 01:03:46,500 Don't wait until you're 40 when it's harder. 1498 01:03:46,500 --> 01:03:47,380 You will need it. 1499 01:03:47,380 --> 01:03:48,880 No matter what field you are in, you 1500 01:03:48,880 --> 01:03:50,850 will need it, so do all of that now. 1501 01:03:50,850 --> 01:03:52,020 OK. 1502 01:03:52,020 --> 01:03:54,000 But to get back to the topic at hand, 1503 01:03:54,000 --> 01:03:57,600 what is the idea behind the Hebb principle? 1504 01:03:57,600 --> 01:04:02,640 The idea is, think about building a house. 1505 01:04:02,640 --> 01:04:04,350 You can't build the first floor if you 1506 01:04:04,350 --> 01:04:06,750 haven't built the foundation. 1507 01:04:06,750 --> 01:04:08,640 Similarly, you might imagine that there 1508 01:04:08,640 --> 01:04:10,950 are lots of aspects of cognition that 1509 01:04:10,950 --> 01:04:14,710 are necessary precursors for other aspects of cognition. 1510 01:04:14,710 --> 01:04:17,353 And if you're wiring up a whole brain, 1511 01:04:17,353 --> 01:04:19,770 you're not going to develop those second order ones if you 1512 01:04:19,770 --> 01:04:21,390 don't get the first order ones. 1513 01:04:21,390 --> 01:04:25,560 And so if you have damage early in life, 1514 01:04:25,560 --> 01:04:29,130 you may have bigger long-term consequences. 1515 01:04:29,130 --> 01:04:31,680 Really concrete kind of silly example. 1516 01:04:31,680 --> 01:04:34,560 Suppose you have damage to primary auditory cortex 1517 01:04:34,560 --> 01:04:36,343 at birth, and you're deaf. 1518 01:04:36,343 --> 01:04:38,760 Well, you're going to have a harder time learning language 1519 01:04:38,760 --> 01:04:41,243 because you need to hear to get language. 1520 01:04:41,243 --> 01:04:42,660 I mean, if you have smart parents, 1521 01:04:42,660 --> 01:04:44,850 they'll teach you sign language, you'll be OK. 1522 01:04:44,850 --> 01:04:47,550 But this is a necessary prior condition. 1523 01:04:47,550 --> 01:04:51,270 And so more generally, it turns out that in a lot of domains, 1524 01:04:51,270 --> 01:04:53,820 some aspects of brain and cognition 1525 01:04:53,820 --> 01:04:56,940 are necessary precursors for others, and in those cases, 1526 01:04:56,940 --> 01:04:59,140 the Kennard Principle doesn't hold. 1527 01:04:59,140 --> 01:04:59,640 OK? 1528 01:05:03,180 --> 01:05:04,230 Blah, blah, blah. 1529 01:05:04,230 --> 01:05:06,090 OK, now let's get-- this is all sort 1530 01:05:06,090 --> 01:05:07,440 of in-principle vague stuff. 1531 01:05:07,440 --> 01:05:10,230 OK, what about visual cortex? 1532 01:05:10,230 --> 01:05:13,080 What about all this stuff we've been talking about here? 1533 01:05:13,080 --> 01:05:15,570 All of these specialized regions for different features 1534 01:05:15,570 --> 01:05:17,040 and different categories, and you 1535 01:05:17,040 --> 01:05:19,470 may notice I've now added visually-presented words 1536 01:05:19,470 --> 01:05:20,190 on there. 1537 01:05:20,190 --> 01:05:23,200 Remember, visually-presented, not auditorily. 1538 01:05:23,200 --> 01:05:24,700 Auditory is a whole different thing. 1539 01:05:24,700 --> 01:05:26,610 This is seeing words and letters. 1540 01:05:26,610 --> 01:05:31,500 OK, so all of this organization, can this stuff move around? 1541 01:05:31,500 --> 01:05:35,940 If you lose this thing, can you regrow it over there? 1542 01:05:35,940 --> 01:05:39,030 Well, not really. 1543 01:05:39,030 --> 01:05:40,860 As I've been talking about, if you 1544 01:05:40,860 --> 01:05:43,530 have brain damage in adulthood, you basically 1545 01:05:43,530 --> 01:05:45,910 lose the corresponding mental function. 1546 01:05:45,910 --> 01:05:48,630 That's why we have all these neuropsychological syndromes. 1547 01:05:48,630 --> 01:05:51,052 If people could relearn and just move the function over, 1548 01:05:51,052 --> 01:05:52,260 you wouldn't have a syndrome. 1549 01:05:52,260 --> 01:05:55,050 You might have a transient problem as you relearned. 1550 01:05:55,050 --> 01:05:57,960 But in fact, if people get achromatopsia-- 1551 01:05:57,960 --> 01:05:59,580 can't see color vision-- 1552 01:05:59,580 --> 01:06:01,890 they're not going to get better, or not much. 1553 01:06:01,890 --> 01:06:03,347 Agnosia, if they can't see shape, 1554 01:06:03,347 --> 01:06:04,680 they're not going to get better. 1555 01:06:04,680 --> 01:06:06,690 Akinetopsia, they can't see motion 1556 01:06:06,690 --> 01:06:08,477 after a stroke in adulthood. 1557 01:06:08,477 --> 01:06:09,810 They're not going to get better. 1558 01:06:09,810 --> 01:06:14,430 Prosopagnosia, topographic disorientation, and alexia-- 1559 01:06:14,430 --> 01:06:16,770 inability to read due to a stroke-- basically, 1560 01:06:16,770 --> 01:06:19,740 people don't really recover from these things. 1561 01:06:19,740 --> 01:06:21,570 There's a beautiful recent article 1562 01:06:21,570 --> 01:06:28,470 by a German neuroscientist who had a stroke 1563 01:06:28,470 --> 01:06:31,350 and couldn't read at-- 1564 01:06:31,350 --> 01:06:34,300 I don't know-- age 50, 60, something like that. 1565 01:06:34,300 --> 01:06:36,510 And so made himself an experimental subject, 1566 01:06:36,510 --> 01:06:39,240 and was just determined to relearn to read. 1567 01:06:39,240 --> 01:06:41,287 And he did every possible thing, and he's 1568 01:06:41,287 --> 01:06:42,870 written about this very interestingly, 1569 01:06:42,870 --> 01:06:45,330 and there's an article I can put on the website 1570 01:06:45,330 --> 01:06:47,280 if anybody wants to read it. 1571 01:06:47,280 --> 01:06:50,040 He basically retaught himself to read, 1572 01:06:50,040 --> 01:06:52,710 but he's doing it in completely different ways 1573 01:06:52,710 --> 01:06:54,390 from what all of you are doing. 1574 01:06:54,390 --> 01:06:55,770 He doesn't have that bit. 1575 01:06:55,770 --> 01:06:57,390 He didn't develop a new one of those. 1576 01:06:57,390 --> 01:07:00,900 He developed a very different compensatory strategy that's 1577 01:07:00,900 --> 01:07:03,030 very slow and doesn't work anywhere near 1578 01:07:03,030 --> 01:07:06,690 as well as reading does for any of us. 1579 01:07:06,690 --> 01:07:10,440 So basically, in adulthood, these things can't move around. 1580 01:07:10,440 --> 01:07:12,690 So now, are we talking Kennard or are we talking Hebb? 1581 01:07:16,170 --> 01:07:19,592 What happens if you get the damage in childhood? 1582 01:07:19,592 --> 01:07:21,300 Well, I'm raising this question because I 1583 01:07:21,300 --> 01:07:23,050 think it's big, and deep, and interesting, 1584 01:07:23,050 --> 01:07:25,770 but there basically isn't much of an answer to it. 1585 01:07:25,770 --> 01:07:26,692 It's hard to answer. 1586 01:07:26,692 --> 01:07:28,150 I'll give you just a shred of data, 1587 01:07:28,150 --> 01:07:30,150 but basically, I think we don't know the answer, 1588 01:07:30,150 --> 01:07:33,480 and I'm dying to know the answer. 1589 01:07:33,480 --> 01:07:35,730 I'll give you just the one paper that I know 1590 01:07:35,730 --> 01:07:37,226 of that's relevant to this. 1591 01:07:37,226 --> 01:07:40,140 This is a study from quite a while ago. 1592 01:07:40,140 --> 01:07:41,760 It's the case of a patient who's known 1593 01:07:41,760 --> 01:07:43,560 in the literature as Adam. 1594 01:07:43,560 --> 01:07:46,920 And Adam sustained bilateral damage 1595 01:07:46,920 --> 01:07:50,280 to his ventral visual pathway, both sides, 1596 01:07:50,280 --> 01:07:53,910 at day one of age due to a stroke. 1597 01:07:53,910 --> 01:07:56,910 Actually, strokes around birth are surprisingly common, 1598 01:07:56,910 --> 01:07:59,100 like this happens. 1599 01:07:59,100 --> 01:08:03,038 So this guy basically lost cortex in a lot of the regions 1600 01:08:03,038 --> 01:08:05,580 that we've been talking about on the bottom of the brain that 1601 01:08:05,580 --> 01:08:07,380 do high-level vision. 1602 01:08:07,380 --> 01:08:11,880 OK, so he was tested for this study at age 16. 1603 01:08:11,880 --> 01:08:14,190 Now, his visual acuity, his ability 1604 01:08:14,190 --> 01:08:16,560 to see fine-grained stuff is not great, 1605 01:08:16,560 --> 01:08:19,590 and his object recognition is not perfect, 1606 01:08:19,590 --> 01:08:21,390 but it's not terrible either. 1607 01:08:21,390 --> 01:08:25,770 He can recognize common objects from photographs and line 1608 01:08:25,770 --> 01:08:27,689 drawings reasonably well. 1609 01:08:27,689 --> 01:08:30,600 So he has some residual vision. 1610 01:08:30,600 --> 01:08:34,750 But he can't recognize faces at all. 1611 01:08:34,750 --> 01:08:39,397 So he is a fan of this TV series called Baywatch, 1612 01:08:39,397 --> 01:08:40,439 which I don't know about. 1613 01:08:40,439 --> 01:08:42,180 I don't know if that's like-- anyway, this study was 1614 01:08:42,180 --> 01:08:43,055 done a long time ago. 1615 01:08:43,055 --> 01:08:46,229 Anyway, some beach TV series that 1616 01:08:46,229 --> 01:08:49,590 has the same set of characters, and he was obsessed with this, 1617 01:08:49,590 --> 01:08:51,720 and he watched it for an hour every day 1618 01:08:51,720 --> 01:08:53,981 for a year and a half. 1619 01:08:53,981 --> 01:08:55,439 And that's just relevant because we 1620 01:08:55,439 --> 01:08:58,560 know that he has lots of experience 1621 01:08:58,560 --> 01:09:01,229 looking at these individuals. 1622 01:09:01,229 --> 01:09:05,250 But when tested in the lab on pictures from Baywatch, 1623 01:09:05,250 --> 01:09:08,279 he couldn't recognize any of the major protagonists. 1624 01:09:08,279 --> 01:09:12,810 That's just a measure of how severely prosopagnosic he was. 1625 01:09:12,810 --> 01:09:16,158 So that suggests that when the relevant parts of the brain, 1626 01:09:16,158 --> 01:09:18,450 that the relevant parts are already specified at birth, 1627 01:09:18,450 --> 01:09:20,992 and if you lose those parts, you can't just put that function 1628 01:09:20,992 --> 01:09:23,189 somewhere else. 1629 01:09:23,189 --> 01:09:25,566 So that suggests-- I'm not leaning too hard on this 1630 01:09:25,566 --> 01:09:27,149 because there's just very little data. 1631 01:09:27,149 --> 01:09:30,479 This is the best there is. 1632 01:09:30,479 --> 01:09:32,100 So it suggests that those-- 1633 01:09:32,100 --> 01:09:36,270 at least the general region is already specified. 1634 01:09:36,270 --> 01:09:38,100 Can anybody think about why that might be? 1635 01:09:38,100 --> 01:09:41,160 Why can't you just train up some other part of cortex? 1636 01:09:41,160 --> 01:09:43,080 Say, his object recognition is pretty good. 1637 01:09:43,080 --> 01:09:46,149 Why can't you train that part of the object recognition system 1638 01:09:46,149 --> 01:09:48,074 and just say, OK, learn to do faces? 1639 01:09:50,767 --> 01:09:52,100 Nobody knows the answer to this. 1640 01:09:52,100 --> 01:09:52,600 Yes. 1641 01:09:52,600 --> 01:09:54,710 AUDIENCE: I don't know about the [INAUDIBLE] 1642 01:09:54,710 --> 01:09:58,300 it's gone completely, just maybe because throughout time 1643 01:09:58,300 --> 01:10:03,363 very far back in evolution, it's a face region. 1644 01:10:03,363 --> 01:10:04,280 NANCY KANWISHER: Yeah. 1645 01:10:04,280 --> 01:10:08,300 Yes, but still-- yeah, I mean, it's clear that we have it, 1646 01:10:08,300 --> 01:10:11,720 and we probably have it for some reason and all of that. 1647 01:10:11,720 --> 01:10:14,870 But why couldn't you just grow a new one over 1648 01:10:14,870 --> 01:10:16,220 in a different part of cortex? 1649 01:10:16,220 --> 01:10:17,810 What's wrong with that other bit of cortex? 1650 01:10:17,810 --> 01:10:19,602 What might it not have that you might need. 1651 01:10:19,602 --> 01:10:20,118 [INAUDIBLE]? 1652 01:10:20,118 --> 01:10:21,410 AUDIENCE: The right connection? 1653 01:10:21,410 --> 01:10:23,258 NANCY KANWISHER: Yes! 1654 01:10:23,258 --> 01:10:24,800 I just showed you guys that there are 1655 01:10:24,800 --> 01:10:26,020 very distinctive connections. 1656 01:10:26,020 --> 01:10:27,020 This is all speculation. 1657 01:10:27,020 --> 01:10:27,860 Nobody knows why. 1658 01:10:27,860 --> 01:10:30,312 I'm just saying that one guess is 1659 01:10:30,312 --> 01:10:32,270 that the reason these things can't just take up 1660 01:10:32,270 --> 01:10:33,812 residence someplace else is they need 1661 01:10:33,812 --> 01:10:39,260 those particular connections to get the right input to process. 1662 01:10:39,260 --> 01:10:42,990 OK, anyway, this is going way beyond the data. 1663 01:10:42,990 --> 01:10:45,740 But in principle, people could get more data of this kind 1664 01:10:45,740 --> 01:10:47,210 and answer this question. 1665 01:10:47,210 --> 01:10:49,490 If I can find the relevant subjects, 1666 01:10:49,490 --> 01:10:51,860 I'm aiming to do this. 1667 01:10:51,860 --> 01:10:53,690 OK, so let's take one other case. 1668 01:10:53,690 --> 01:10:58,383 Very different kind of change to ask, what happens-- 1669 01:10:58,383 --> 01:11:00,050 so basically, bottom line of all of this 1670 01:11:00,050 --> 01:11:03,170 is, stuff doesn't move around that much. 1671 01:11:03,170 --> 01:11:05,450 Early brain damage to language regions, 1672 01:11:05,450 --> 01:11:07,280 they can shift to the homologous regions 1673 01:11:07,280 --> 01:11:08,940 in the right hemisphere. 1674 01:11:08,940 --> 01:11:10,488 But all the other data that I know of 1675 01:11:10,488 --> 01:11:12,530 suggests you can't just take anything and move it 1676 01:11:12,530 --> 01:11:15,350 around a few centimeters over. 1677 01:11:15,350 --> 01:11:17,630 At least if you have the damage in adulthood, 1678 01:11:17,630 --> 01:11:20,090 and maybe even if you have it pretty early. 1679 01:11:20,090 --> 01:11:21,500 OK, all right. 1680 01:11:21,500 --> 01:11:25,310 So now we're going to say, OK, might this organization 1681 01:11:25,310 --> 01:11:27,350 nonetheless be very different if you 1682 01:11:27,350 --> 01:11:30,080 had very different experience? 1683 01:11:30,080 --> 01:11:34,550 So let's take the case of congenital blindness. 1684 01:11:34,550 --> 01:11:36,080 OK, so how is the brain organized 1685 01:11:36,080 --> 01:11:38,960 in congenital blindness? 1686 01:11:38,960 --> 01:11:40,520 Well, let's take V1. 1687 01:11:40,520 --> 01:11:43,340 Here's this big chunk of cortex back here, nice 1688 01:11:43,340 --> 01:11:47,795 big chunk of cortex that, in all of you guys, does vision. 1689 01:11:47,795 --> 01:11:49,670 What does it do in congenitally blind people? 1690 01:11:49,670 --> 01:11:50,628 Does it just sit there? 1691 01:11:50,628 --> 01:11:51,560 Do the cells die out? 1692 01:11:51,560 --> 01:11:53,090 Do they just go dum-dee-dum-dee-dum and they 1693 01:11:53,090 --> 01:11:53,840 don't do anything? 1694 01:11:53,840 --> 01:11:57,900 It's a lot of cortex to waste on all of that. 1695 01:11:57,900 --> 01:12:00,290 Well, it turns out, astonishingly, 1696 01:12:00,290 --> 01:12:02,570 that what visual cortex does in blind people 1697 01:12:02,570 --> 01:12:04,140 is a whole bunch of other things, 1698 01:12:04,140 --> 01:12:08,300 including, astonishingly, language. 1699 01:12:08,300 --> 01:12:11,120 So you present a sentence to subjects through Braille 1700 01:12:11,120 --> 01:12:13,730 or auditorily to blind subjects in the scanner, 1701 01:12:13,730 --> 01:12:17,460 and you see activation of V1. 1702 01:12:17,460 --> 01:12:22,550 Further, you might think, well, OK, whatever. 1703 01:12:22,550 --> 01:12:25,760 Just turns on, it has nothing to do with anything. 1704 01:12:25,760 --> 01:12:29,990 But TMS studies-- V1 is right near the surface of the brain. 1705 01:12:29,990 --> 01:12:32,870 You can zap that region and ask if you're disrupting function, 1706 01:12:32,870 --> 01:12:34,760 and you can interfere with language task 1707 01:12:34,760 --> 01:12:37,830 by zapping V1 in congenitally blind people. 1708 01:12:37,830 --> 01:12:39,410 So it's not just activated. 1709 01:12:39,410 --> 01:12:42,320 It's doing causal work in blind people. 1710 01:12:42,320 --> 01:12:43,790 This is mind-blowing. 1711 01:12:43,790 --> 01:12:49,040 This is like a totally different patch of cortex. 1712 01:12:49,040 --> 01:12:51,560 So yeah, it's hard to think of more different functions 1713 01:12:51,560 --> 01:12:55,160 than low-level vision and high-level abstract language 1714 01:12:55,160 --> 01:12:57,020 processing. 1715 01:12:57,020 --> 01:13:01,100 So that suggests radical possible reorganization, 1716 01:13:01,100 --> 01:13:03,050 in this case, with different experience. 1717 01:13:07,080 --> 01:13:09,958 OK, what about those regions on the bottom surface 1718 01:13:09,958 --> 01:13:10,500 of the brain? 1719 01:13:10,500 --> 01:13:13,740 The face, place, word, and body regions 1720 01:13:13,740 --> 01:13:15,810 that we've been talking about for so long. 1721 01:13:15,810 --> 01:13:17,352 What do they do in blind people? 1722 01:13:17,352 --> 01:13:19,560 Somebody already asked me before, maybe [INAUDIBLE].. 1723 01:13:19,560 --> 01:13:20,393 Somebody over there. 1724 01:13:20,393 --> 01:13:23,310 It's my spatial code. 1725 01:13:23,310 --> 01:13:26,100 And there's a lot of claims that they 1726 01:13:26,100 --> 01:13:29,850 have similar selectivity, which I'm not totally sure of, 1727 01:13:29,850 --> 01:13:35,460 but let me show you one piece of data. 1728 01:13:35,460 --> 01:13:36,960 I promised you that there were going 1729 01:13:36,960 --> 01:13:41,340 to be further contradictions in the whole saga of the role 1730 01:13:41,340 --> 01:13:43,210 of experience in wiring up these regions, 1731 01:13:43,210 --> 01:13:46,327 so here's one more contradictory piece of data. 1732 01:13:46,327 --> 01:13:48,660 OK, this is a paper that was published just a few months 1733 01:13:48,660 --> 01:13:52,410 ago, and the title of the paper is that the development 1734 01:13:52,410 --> 01:13:55,230 of visual category selectivity-- that means face place body 1735 01:13:55,230 --> 01:13:56,550 regions, all that stuff-- 1736 01:13:56,550 --> 01:13:59,490 in the ventral visual cortex does not 1737 01:13:59,490 --> 01:14:02,100 require visual experience. 1738 01:14:02,100 --> 01:14:03,370 OK. 1739 01:14:03,370 --> 01:14:04,144 What? 1740 01:14:04,144 --> 01:14:07,230 What, what, what? 1741 01:14:07,230 --> 01:14:08,690 OK, here's what they did. 1742 01:14:08,690 --> 01:14:10,500 They scanned-- pretty crazy experiment-- 1743 01:14:10,500 --> 01:14:14,400 they scanned congenitally blind subjects while they heard 1744 01:14:14,400 --> 01:14:17,460 sounds that were associated with faces, bodies, objects, 1745 01:14:17,460 --> 01:14:18,340 and scenes. 1746 01:14:18,340 --> 01:14:21,960 So for example, they might hear laughing, chewing, blowing 1747 01:14:21,960 --> 01:14:23,280 a kiss, whistling sounds. 1748 01:14:23,280 --> 01:14:24,840 Those are face-related sounds. 1749 01:14:24,840 --> 01:14:28,470 Or they might hear scratching, hand-clapping, finger-snapping, 1750 01:14:28,470 --> 01:14:30,360 bare footsteps, knuckle cracking. 1751 01:14:30,360 --> 01:14:32,710 Those are body-related sounds, et cetera. 1752 01:14:32,710 --> 01:14:36,720 So they're lying in the scanner hearing these sounds. 1753 01:14:36,720 --> 01:14:38,370 Probably cracking up. 1754 01:14:38,370 --> 01:14:43,110 Now the question is, do we see face, place, body, 1755 01:14:43,110 --> 01:14:46,290 and object regions activated from sounds 1756 01:14:46,290 --> 01:14:48,090 in congenitally blind people listening 1757 01:14:48,090 --> 01:14:50,730 to those categories of sounds? 1758 01:14:50,730 --> 01:14:54,400 And the crazy answer is, kind of sort of a little bit. 1759 01:14:54,400 --> 01:14:55,590 It's not super strong. 1760 01:14:55,590 --> 01:14:57,940 The data are not mind-blowing, but let 1761 01:14:57,940 --> 01:14:59,190 me just show you what we have. 1762 01:14:59,190 --> 01:15:01,482 OK, this is the bottom of the brain, back of the brain. 1763 01:15:01,482 --> 01:15:03,150 Everybody oriented here? 1764 01:15:03,150 --> 01:15:03,870 OK. 1765 01:15:03,870 --> 01:15:04,542 Occipital lobe. 1766 01:15:04,542 --> 01:15:06,000 This is where all the good stuff is 1767 01:15:06,000 --> 01:15:07,250 that we've been talking about. 1768 01:15:07,250 --> 01:15:07,890 OK. 1769 01:15:07,890 --> 01:15:10,800 So this is now the sighted control subjects 1770 01:15:10,800 --> 01:15:12,900 looking at visual stimuli. 1771 01:15:12,900 --> 01:15:15,790 So this is a significant map, P levels. 1772 01:15:15,790 --> 01:15:19,260 And so what you see is facial activity in red, 1773 01:15:19,260 --> 01:15:22,350 object selectivity in green, scene selectivity 1774 01:15:22,350 --> 01:15:25,810 in blue, purple, whatever that is-- blue. 1775 01:15:25,810 --> 01:15:28,230 So that should look sort of familiar. 1776 01:15:28,230 --> 01:15:31,230 Faces, lateral, scenes, medial. 1777 01:15:31,230 --> 01:15:32,848 Objects, people debate about. 1778 01:15:32,848 --> 01:15:35,140 I haven't talked about it much, because-- anyway, faces 1779 01:15:35,140 --> 01:15:37,500 and scenes, so stuff to pay attention to. 1780 01:15:37,500 --> 01:15:39,360 OK. 1781 01:15:39,360 --> 01:15:42,150 And over here-- this map is the same. 1782 01:15:42,150 --> 01:15:44,550 It just says, never mind if that voxel reaches 1783 01:15:44,550 --> 01:15:45,960 statistical significance. 1784 01:15:45,960 --> 01:15:50,760 Just plot what category that voxel responds most to. 1785 01:15:50,760 --> 01:15:53,220 So you just see a big swath. 1786 01:15:53,220 --> 01:15:53,970 All right. 1787 01:15:53,970 --> 01:15:57,660 Now, what do we see for sighted controls listening 1788 01:15:57,660 --> 01:16:00,000 to the auditory stimuli? 1789 01:16:00,000 --> 01:16:02,970 Not much reaches significance. 1790 01:16:02,970 --> 01:16:05,270 If you drop the threshold way down and look at this, 1791 01:16:05,270 --> 01:16:06,910 maybe a little bit. 1792 01:16:06,910 --> 01:16:10,050 These are somewhat correlated, but it's lousy. 1793 01:16:10,050 --> 01:16:14,370 So sighted subjects listening to those sounds, not much. 1794 01:16:14,370 --> 01:16:16,840 What do you think happens with blind subjects listening 1795 01:16:16,840 --> 01:16:19,830 to those sounds? 1796 01:16:19,830 --> 01:16:23,400 Well, you get face selectivity here 1797 01:16:23,400 --> 01:16:25,480 that's statistically significant. 1798 01:16:25,480 --> 01:16:28,170 And if you drop the threshold and look at the overall map, 1799 01:16:28,170 --> 01:16:30,690 you see a resemblance of this map 1800 01:16:30,690 --> 01:16:33,990 to the sighted map, the visual map in the sighted subjects, 1801 01:16:33,990 --> 01:16:37,540 and this correlation is highly significant. 1802 01:16:37,540 --> 01:16:40,950 So this is totally weird. 1803 01:16:40,950 --> 01:16:43,740 It says, yes, there's a similar spatial layout 1804 01:16:43,740 --> 01:16:47,580 on the brain of these same selectivities in congenitally 1805 01:16:47,580 --> 01:16:49,635 blind subjects who never saw those stimuli. 1806 01:16:52,170 --> 01:16:54,030 And that's the basis of their argument, 1807 01:16:54,030 --> 01:16:57,960 that the development of visually category selectivity 1808 01:16:57,960 --> 01:17:00,450 doesn't require experience. 1809 01:17:00,450 --> 01:17:03,570 But now you may be thinking, what about that paper 1810 01:17:03,570 --> 01:17:05,880 on face-deprived monkeys? 1811 01:17:05,880 --> 01:17:08,310 The title of which is, "Seeing faces 1812 01:17:08,310 --> 01:17:11,820 is necessary for face-domain formation," 1813 01:17:11,820 --> 01:17:14,020 namely for face patches. 1814 01:17:14,020 --> 01:17:16,950 So these two findings, these two claims in the titles 1815 01:17:16,950 --> 01:17:20,130 are completely contradictory. 1816 01:17:20,130 --> 01:17:21,330 So we're out of time. 1817 01:17:21,330 --> 01:17:22,740 Nobody knows the answer to this. 1818 01:17:22,740 --> 01:17:24,100 It's an ongoing puzzle. 1819 01:17:24,100 --> 01:17:25,830 There are all kinds of possibilities. 1820 01:17:25,830 --> 01:17:27,270 They're different species, they're 1821 01:17:27,270 --> 01:17:28,350 different kinds of tests. 1822 01:17:28,350 --> 01:17:29,970 There are many things you could say, 1823 01:17:29,970 --> 01:17:32,670 but we're really right on the horn of a big conundrum 1824 01:17:32,670 --> 01:17:33,750 in the field. 1825 01:17:33,750 --> 01:17:36,210 And all I have to say is welcome to the cutting edge. 1826 01:17:36,210 --> 01:17:37,500 It's a mess there. 1827 01:17:37,500 --> 01:17:39,590 OK, thank you.