1 00:00:00,970 --> 00:00:08,350 To the Oxford Playhouse. My name is Marcus Otellini, the summoning professor for the public understanding of science here in Switzerland. 2 00:00:08,860 --> 00:00:14,890 Welcome to this hour of Premier Events, University of Oxford for engagement in science at the public. 3 00:00:15,130 --> 00:00:18,760 We're right back. Back at the Playhouse in the newly refurbished seats. 4 00:00:18,760 --> 00:00:23,709 I'd be trying to work out some patterns so they are not completely fox me. 5 00:00:23,710 --> 00:00:30,250 So I'll be the desk expansion of PI, but it's great to have such a one for audience. 6 00:00:30,570 --> 00:00:35,830 Also like to thank the Common Law Foundation who financially make this possible as well. 7 00:00:36,100 --> 00:00:44,889 And I think it's testament to the subjects that will be addressed tonight that this probably has been the fastest selling, 8 00:00:44,890 --> 00:00:51,490 so many lecture I've been involved in because that the topic that we're going to be talking about is the subject of autism, 9 00:00:51,490 --> 00:00:55,389 which obviously affects many people in our society. 10 00:00:55,390 --> 00:01:01,330 But it's maybe I shouldn't say, unfortunately, and that's somehow I think the what we're going to be exploring. 11 00:01:01,330 --> 00:01:08,739 We have great, fantastic speakers. Simon Baron-Cohen, who is our of the centre, the Autism Research Centre in Cambridge. 12 00:01:08,740 --> 00:01:16,630 He's of Trinity College, Cambridge. And I first met him actually, because I think that's the moment. 13 00:01:16,960 --> 00:01:26,470 We often kind of slightly joke about the importance of the kind of Asperger's autistic spectrum that it is the other departments in this university. 14 00:01:26,470 --> 00:01:32,530 And I say, remember an interview a few years ago with one of my colleagues actually when I was at Cambridge, 15 00:01:33,370 --> 00:01:41,770 Richard Dawkins, who was being interviewed by Simon Singh in The Guardian after he'd won Nobel Prize, the Fields Medal. 16 00:01:42,400 --> 00:01:45,580 And he sort of confessed to Simon that, well, 17 00:01:45,580 --> 00:01:53,230 I worked on this kind of scale of athletics and I scored five out of the six key indicate the science, but he's kind of self-diagnosed himself. 18 00:01:53,830 --> 00:01:57,309 And Simon picked this up and one of his books, 19 00:01:57,310 --> 00:02:04,570 which I really enjoyed reading The Essential Difference Exploring what makes an autistic brain slightly different. 20 00:02:04,570 --> 00:02:12,370 What is the Defining Factor? Actually dedicated a chapter to exploring whether Richard Wolff, in fact, is vertical or not. 21 00:02:12,970 --> 00:02:20,650 And that's really at the heart of the talk today, because we're going to be exploring the question of autism and why, why the science. 22 00:02:20,650 --> 00:02:24,280 So, you know, it's actually a positive trait for us. 23 00:02:24,280 --> 00:02:28,630 Mathematicians have a great message. Welcome to Simon Baron-Cohen. 24 00:02:36,840 --> 00:02:43,530 Very much. It's a great pleasure to be back in Oxford. I was a student of some capacity as a good citizen. 25 00:02:43,730 --> 00:02:48,390 Nostalgia. Well, getting off the train, coming back into this beautiful city. 26 00:02:49,180 --> 00:02:53,850 I want to thank the organisers of this lecture. 27 00:02:54,340 --> 00:02:57,720 Invited me to give a talk in this series. 28 00:02:58,560 --> 00:03:02,459 It feels like an honour. This afternoon. 29 00:03:02,460 --> 00:03:11,280 This evening, I'll be exploring this topic of autism, but its connection to scientific talent. 30 00:03:15,970 --> 00:03:23,650 So I thought I'd start just with an image of almost a stereotype of a child with autism. 31 00:03:24,490 --> 00:03:30,910 Because sometimes a picture says more than words can. So what we see is a boy. 32 00:03:31,180 --> 00:03:37,390 And I notice it affects boys much more often than girls and boys playing alone. 33 00:03:38,470 --> 00:03:45,670 And part of the diagnosis of autism are difficulties in social interaction and in communication. 34 00:03:46,630 --> 00:03:51,460 But you can also see in this picture that he's doing something intelligent. 35 00:03:51,940 --> 00:03:56,770 He's lining up his toys in a very precise way, but he's making patterns. 36 00:03:57,520 --> 00:04:08,050 And those of you who live with autism, live with someone with autism, know that people with autism, love persons, they love order their universe. 37 00:04:08,560 --> 00:04:13,420 And what upsets the most is if someone comes along and disturbs that perfect order. 38 00:04:14,350 --> 00:04:22,090 But either way, what we're seeing is in some respects a disability struggling with socialisation. 39 00:04:22,510 --> 00:04:26,560 But in other respects, a mind that is very precise and very ordered. 40 00:04:28,990 --> 00:04:31,390 Here's one more child with autism. 41 00:04:32,860 --> 00:04:44,260 And this child is playing with water and is fascinated by how the patterns of water droplets change as he blocks the flow of water with his hands. 42 00:04:44,890 --> 00:04:49,600 So again, we're seeing a child who in one context struggles. 43 00:04:50,260 --> 00:04:57,250 We shouldn't lose sight of the disability. But left to their own devices, they have a fascination with patterns. 44 00:04:57,610 --> 00:05:05,110 And that's really the topic I want to discuss. Before I do that, a little bit about the background to autism, 45 00:05:05,680 --> 00:05:14,510 because this graph shows you that autism has been diagnosed increasingly, often year by year. 46 00:05:14,860 --> 00:05:23,799 The data here goes from 1996 through 2005, just showing you the number of cases per thousand being diagnosed. 47 00:05:23,800 --> 00:05:28,360 So it's been a steady increase and some people have wondered what's driving this. 48 00:05:29,170 --> 00:05:35,410 And in all likelihood, it's quite ordinary factors that we're just getting more aware of autism, 49 00:05:36,100 --> 00:05:42,670 but we are getting better at recognising it that there are more services on the ground looking for it. 50 00:05:43,750 --> 00:05:53,230 But also we've brought it into our definition of autism, particularly to include a subgroup called Asperger's Syndrome that Marcus just referred to. 51 00:05:53,740 --> 00:05:57,700 So we've landed another subgroup and that will, of course inflate the numbers. 52 00:05:59,200 --> 00:06:09,850 That's the data up to 2005. And you can see that this next graph takes us a bit further from 2006 up to 2012, that increase has continued. 53 00:06:10,000 --> 00:06:16,330 So you might be wondering, where is this leading? Autism is being diagnosed more and more. 54 00:06:16,930 --> 00:06:21,100 And I think this is a good thing because the diagnosis, when it's done properly, 55 00:06:22,180 --> 00:06:25,540 is done for a reason, which is to help individuals who are struggling. 56 00:06:26,760 --> 00:06:31,530 So I think we're getting closer to recognising all of the individuals that need that support. 57 00:06:32,250 --> 00:06:41,790 I don't think we're over diagnosing. But I suppose the other trends that comes out from these two prompts is that in the old days, 58 00:06:41,790 --> 00:06:47,100 and this is when I started doing autism research, the condition was thought to be very rare. 59 00:06:48,030 --> 00:06:50,730 They used to say four in 10,000 children. 60 00:06:51,180 --> 00:07:01,860 Nowadays, if I go to the most up to date data, so this is 2014 published data from the states, from the Centre for Disease Control. 61 00:07:02,270 --> 00:07:05,550 The Americans regard this as a disease or a disorder. 62 00:07:06,580 --> 00:07:15,570 And you can see that the current figures are one in 48 points and one in 189 girls. 63 00:07:16,020 --> 00:07:19,020 So we're still seeing autism being more common in boys. 64 00:07:19,710 --> 00:07:24,090 If you average across the two genders, it comes out to one in 68. 65 00:07:24,630 --> 00:07:27,610 So it's no longer rare. It's actually very common. 66 00:07:28,780 --> 00:07:39,780 I found the graph in a way shows you autism in a snapshot because it also shows that some people on the autism spectrum, 67 00:07:39,780 --> 00:07:44,700 as it's called, also have learning difficulties that delay in development. 68 00:07:44,970 --> 00:07:48,000 Well, generally, they may even have language delay. 69 00:07:48,930 --> 00:07:54,960 And that's true both in the boys and the girls. There's a proportion who have learning difficulties as well. 70 00:07:55,350 --> 00:08:01,200 But you couldn't have autism without certainly learning difficulties without any delay in your development. 71 00:08:01,770 --> 00:08:04,890 So average IQ, even above average IQ. 72 00:08:05,250 --> 00:08:08,790 And that's really what creates this breadth of the spectrum. 73 00:08:10,920 --> 00:08:17,010 So under this term, the autism spectrum was coined, goes back to 1998. 74 00:08:17,790 --> 00:08:25,470 We thought this was very interesting, the idea that there might be a spectrum of autistic traits and thoughts about how we could measure it. 75 00:08:26,760 --> 00:08:36,450 So Mark has just mentioned this questionnaire. The Rich Abortions has taken a big hit on the autism spectrum questions. 76 00:08:37,320 --> 00:08:46,110 So you can find it on the Web. You can place it and see how many autistic traits you have on the dotted line. 77 00:08:46,610 --> 00:08:54,180 On the left bell curve shows that autistic traits are normally distributed throughout the population. 78 00:08:54,300 --> 00:09:02,129 We all have some. So there's a bell curve and the solid line on the right of the scores that people 79 00:09:02,130 --> 00:09:06,780 who end up with a diagnosis shape the distribution of scores that they have. 80 00:09:07,260 --> 00:09:11,050 And again, even within the clinic, you see a range of scores. 81 00:09:11,370 --> 00:09:17,880 I should help you to read this by saying along the horizontal axis, the x axis, it goes from zero 3 to 50. 82 00:09:18,750 --> 00:09:25,250 And if you're scoring very high so you're shifted over towards the right, that graph you may need to diagnosis, 83 00:09:25,650 --> 00:09:31,680 but it's only when these trips are interfering with your ability to cope in life, 84 00:09:32,310 --> 00:09:36,000 whether as a child or as or an adult, that you would need a diagnosis. 85 00:09:36,240 --> 00:09:42,390 Otherwise these traits are just there and they might have some adaptive or positive characteristics. 86 00:09:44,520 --> 00:09:49,710 So what else do we know about autism? Well, the first thing is we know that it's partly genetic. 87 00:09:50,520 --> 00:09:56,900 So here we've got an image of a family where one of the children has autism. 88 00:09:57,570 --> 00:10:01,020 What we know is that if one child in the family has autism, 89 00:10:01,500 --> 00:10:07,770 the likelihood of another child in the same family also receiving a diagnosis is one in three. 90 00:10:09,060 --> 00:10:16,110 So although in the general population it's about 1%, as soon as you've got a family relative with the diagnosis, 91 00:10:16,590 --> 00:10:21,610 your odds of getting of getting diagnosed dramatically shapes up. 92 00:10:21,940 --> 00:10:24,450 And we think that that's to do with genetics. 93 00:10:25,890 --> 00:10:35,160 The reason we think that these days you can look at the genome and the picture on the top here shows you the human chromosomes, 94 00:10:35,880 --> 00:10:47,400 23 pairs of chromosomes. But each little jumps on the chromosomes is a genetic association that's been reported in the scientific literature. 95 00:10:48,620 --> 00:10:53,669 This is being constantly updated on the website that is showing the time to change 96 00:10:53,670 --> 00:11:00,890 on Safari World because almost every week in one of the scientific journals, 97 00:11:01,070 --> 00:11:06,680 there will be a new report about a genetic discovering genes associated with autism. 98 00:11:07,040 --> 00:11:12,200 When I last looked over 400 genes that have been identified as linked to autism. 99 00:11:12,650 --> 00:11:17,330 So we know we're talking about a complex condition in terms of it being polygenic. 100 00:11:18,470 --> 00:11:26,330 And we know that these genes are literally found right across the gene in every human chromosome. 101 00:11:27,590 --> 00:11:30,440 You can see that a lot of these genes are expressed in the brain. 102 00:11:30,800 --> 00:11:38,840 So this this image superimposes gene expression amongst some of those genes that have 103 00:11:38,840 --> 00:11:43,400 been identified as linked to autism are those ones that are found in the brain, 104 00:11:44,150 --> 00:11:49,610 again, published in our high profile journals and the scientific world. 105 00:11:51,110 --> 00:12:00,230 So I mentioned that autism is partly genetic, not completely genetic, because you can have identical twins like these sisters. 106 00:12:00,810 --> 00:12:08,780 One has autism and one doesn't. So the very existence of so-called discordant pairs of twins, 107 00:12:09,620 --> 00:12:15,890 even though that genetic identical one has one, doesn't mean that genes company the whole story. 108 00:12:16,340 --> 00:12:21,290 There must be environmental factors that interact with your genetic predisposition. 109 00:12:22,430 --> 00:12:26,150 We don't have such a good handle on what those genetic factors are. 110 00:12:26,840 --> 00:12:31,430 But suffice it to say that twin studies just make it. 111 00:12:31,790 --> 00:12:36,920 They make the argument that environment must also be interacting with genetics. 112 00:12:39,550 --> 00:12:44,280 So I've mentioned that autism entails disability, but I don't want to lose sight of that. 113 00:12:45,340 --> 00:12:49,330 But when you have your diagnosis, it's because you really need it. 114 00:12:49,390 --> 00:12:58,750 Well, we're struggling. And universities like optimism of students with autism who hopefully find their way to the disability resource, 115 00:12:59,920 --> 00:13:06,760 will get extra support because of that disability. And that disability is very much in the realm of social interaction. 116 00:13:07,300 --> 00:13:13,780 What we know is that there's difficulties or differences in ability to cope with the social world. 117 00:13:14,050 --> 00:13:22,210 Start very early. This is a study looking at brain activity in babies where there's already a child with autism. 118 00:13:22,510 --> 00:13:27,640 So they're tracking the next child in the family who's a genetic risk of autism. 119 00:13:28,600 --> 00:13:33,999 And just looking at whether they showed the expected pattern of brain activity when they're looking 120 00:13:34,000 --> 00:13:39,790 at a face or the eyes are either directed straight at the child or looking away from the child. 121 00:13:40,180 --> 00:13:49,060 In a typical child we operate in, a child's brain is exquisitely sensitive to whether they're being looked at or not being looked at. 122 00:13:49,240 --> 00:13:58,660 We pay a lot of attention to faces, but we find that in children with autism or children who have a risk of autism and for genetic reasons, 123 00:13:59,110 --> 00:14:07,990 perhaps brain activity is different. It's reduced in response to changes in looking at someone else's gaze. 124 00:14:09,010 --> 00:14:13,000 So that's very early on, even as young as six months old. 125 00:14:15,340 --> 00:14:21,400 This study comes from California University of California at San Diego, where they took children. 126 00:14:21,910 --> 00:14:25,930 At the earliest point, you can diagnose autism, which is about ten years old, 127 00:14:26,890 --> 00:14:33,730 and they presented children coming into the clinic either with a human face to the at or a geometric design. 128 00:14:34,600 --> 00:14:43,750 And they simply measured how long the child looks tonight that the social stimulus, the human face or the non-social stimulus, the geometric design. 129 00:14:44,530 --> 00:14:51,219 What they found was that if a child looks for more than 70% of the time after a long social stimulus, 130 00:14:51,220 --> 00:14:56,680 the geometric design, the probability that that child has autism was 100%. 131 00:14:57,700 --> 00:15:07,060 So when I read this article, I was quite impressed that there might be a behavioural test that could be used to diagnose autism. 132 00:15:07,690 --> 00:15:11,020 So there's a little caveat here before I go into that. 133 00:15:12,160 --> 00:15:18,130 I suppose what we're seeing is that the typical child, again, has a lot of attention to faces. 134 00:15:18,160 --> 00:15:20,520 Faces are important in our department, 135 00:15:20,980 --> 00:15:29,610 but these kids who go on to develop consciously or receive a diagnosis of autism may be less interested in faces, more interested in patterns. 136 00:15:30,760 --> 00:15:40,910 But what's the caveats about this diagnostic test? Well, if you drill down into the data, you actually see each of these dots is a child. 137 00:15:41,440 --> 00:15:46,660 And they've been assigned to two different groups. The autism group, the red dots, 138 00:15:47,750 --> 00:15:55,120 the horizontal line going across the screen shows you if you're looking more at the geometric patterns rather than faces, 139 00:15:55,510 --> 00:15:59,110 if you're off that line, you're looking more than 70% of the time. 140 00:15:59,670 --> 00:16:05,200 That's geometric design. And so you can see it's true. There's a lot more of those red dots above the line. 141 00:16:05,950 --> 00:16:10,540 So a lot of children with autism would get picked up using this behavioural test. 142 00:16:10,870 --> 00:16:16,810 But equally as mathematicians or those who love statistics in the audience, 143 00:16:17,200 --> 00:16:26,530 we'll say that there's a wide range when it's a lot of kids who the red dots below the line, which means that they will be missed by this test. 144 00:16:26,980 --> 00:16:31,120 So let's interpret some of these scientific findings with caution. 145 00:16:31,510 --> 00:16:40,450 But either way, it's telling us that as a group, children with autism seem to be more biased towards the pencils than they are with that faces. 146 00:16:43,530 --> 00:16:47,960 This is a study that came from Yale University where they used case tracking. 147 00:16:48,780 --> 00:16:54,330 So this time what they're doing is putting the child in front of a computer while they're watching a movie. 148 00:16:54,840 --> 00:16:59,610 And the computer can track what the person's if they're closely watching the movie. 149 00:17:00,150 --> 00:17:09,510 So the red and yellow persons that you see on Elizabeth Taylor's face as they're watching the movie Who's Afraid of Virginia Woolf? 150 00:17:10,200 --> 00:17:17,640 The yellow person is where the typical viewer is watching or looking, really looking at the eye region of the face. 151 00:17:18,210 --> 00:17:27,000 The red area in this image is where people with autism tend to look a lot less at the eyes and more at the mouth whilst they're watching the movie. 152 00:17:27,450 --> 00:17:32,250 So again, we're seeing differences in how people with autism look at faces. 153 00:17:32,820 --> 00:17:42,210 They may not be showing the typical profile, a typical person of attention when they are presented with such information. 154 00:17:46,090 --> 00:17:55,690 So if we should be kind of developmental approach to thinking about children, child's development and social understanding. 155 00:17:56,680 --> 00:18:02,860 If you're not looking so much faces and if you're not really thinking about people as much as a typical child, 156 00:18:03,280 --> 00:18:06,330 that might mean that you're too lazy to go to apartments. 157 00:18:06,820 --> 00:18:12,100 And what's called theory of Mind, being able to imagine what other people are thinking or feeling, 158 00:18:12,640 --> 00:18:17,140 you have to put yourself into someone else's shoes and take someone else's perspective. 159 00:18:17,650 --> 00:18:19,540 That's exactly what's found in autism. 160 00:18:20,320 --> 00:18:29,950 These children struggle to keep track of who knows what or what other people's motives are and ordinary things like hide and seek, 161 00:18:29,950 --> 00:18:37,479 where there's an element of deception in which the typical child loves to engage in games that leave the child with autism, 162 00:18:37,480 --> 00:18:42,430 often feeling confused, stressed, and they prefer to just withdraw. 163 00:18:42,760 --> 00:18:50,690 It's the more predictable ones of patterns. We're trying to track what's going on in the brain, 164 00:18:51,710 --> 00:18:59,120 which is different in autism compared to a typical person when they're asked to look at the eye region of the face. 165 00:18:59,870 --> 00:19:03,740 So up above, we showed people photographs of the eye region. 166 00:19:04,310 --> 00:19:11,420 We asked them to pick which of these four words best describes what the person in the photo is thinking or feeling. 167 00:19:12,410 --> 00:19:16,070 So this is a tough test. All you've got is the eyes. 168 00:19:16,790 --> 00:19:20,450 The correct answer here is that she's a bit dispirited or a bit sad. 169 00:19:21,110 --> 00:19:24,440 I can see some of you nodding, suggesting that you got that one right. 170 00:19:26,990 --> 00:19:31,290 It's tough because all four words describe possible steps applied. 171 00:19:31,290 --> 00:19:35,780 And it's tough because the black and white photo is not very high resolution. 172 00:19:36,740 --> 00:19:41,060 It's tough because you've only got a fragment of information. You don't have the whole facial expression. 173 00:19:41,840 --> 00:19:46,700 What you can see in the graph is that people with autism scored no on this test. 174 00:19:47,690 --> 00:19:54,620 Those are the two parts. There's a fair amount surface left at that graph compared to typical males and females. 175 00:19:54,960 --> 00:20:00,620 This was quite a large dataset because we collected the dinosaur wrong line when we asked people to take 176 00:20:00,620 --> 00:20:06,650 that test whilst they're lying in a scanner for a brain scan so we can look at patterns of brain activity. 177 00:20:07,400 --> 00:20:11,180 We also see a difference in the typical population. 178 00:20:11,510 --> 00:20:17,300 We see a lot of activity in a part of the frontal lobe, the left inferior frontal gyrus. 179 00:20:17,720 --> 00:20:24,020 We find reduced activity in the autistic brain when they're looking at these facial expressions, 180 00:20:24,020 --> 00:20:28,280 just the eyes to try to decode what someone else is thinking or feeling. 181 00:20:29,240 --> 00:20:39,380 So that's showing some of the disability in autism we're also aware of is that when we look at the brain in autism, 182 00:20:39,920 --> 00:20:45,350 we don't see evidence that things are broken or disorders or dysfunctional. 183 00:20:45,770 --> 00:20:51,320 We actually simply see difference. The autistic brain is just developing differently. 184 00:20:51,980 --> 00:21:00,620 And this is a thing that I want to build on. So I'm going to show you some of these differences as part of the journey into understanding autism. 185 00:21:02,390 --> 00:21:07,040 So this study is looking at one particular structure in the brain, the amygdala. 186 00:21:07,400 --> 00:21:13,850 Some people think if you make to the house the emotion centre of the brain, deep in the brain, 187 00:21:13,940 --> 00:21:21,470 below the cortex, and this structure is larger in children with autism compared to typical children. 188 00:21:22,280 --> 00:21:26,750 So what we're seeing is a difference in the volume of a particular region of the brain. 189 00:21:27,260 --> 00:21:30,640 It's not a sign that anything is dysfunctional or diseased, 190 00:21:31,190 --> 00:21:40,220 but this is why we should start challenging the perception or the label that autism is a disorder, because what we're seeing is difference. 191 00:21:43,040 --> 00:21:46,759 It's a bit more evidence for the idea that autism entails. 192 00:21:46,760 --> 00:21:49,500 Just a different person brings about lives. 193 00:21:51,260 --> 00:22:03,230 So the graph on the left, which is where each chart is a child's and they have two brain scans during that, during that childhood. 194 00:22:03,920 --> 00:22:10,070 So what that means is you can track how the brain is growing. You're looking at brain development or brain growth. 195 00:22:10,490 --> 00:22:19,640 You can join the dots to see if the typical group shown in blue or the autism green shirt in red differ in terms of like blindness. 196 00:22:20,490 --> 00:22:27,200 But what you can say is that there is indeed a difference. So this is just showing the total amount of grey matter in the brain. 197 00:22:27,530 --> 00:22:37,100 So again, just looking at some aspect of the volume of the brain and that this is quite early in development during the first five years of life. 198 00:22:37,760 --> 00:22:44,030 The autistic brain is larger at each of those timepoints than the typical brain on average. 199 00:22:44,480 --> 00:22:47,510 So the brain in autism seems to be growing faster. 200 00:22:48,600 --> 00:22:55,590 And larger in typical development. Again, not a sign of disease or pathology. 201 00:22:56,190 --> 00:23:03,360 Simply a different pattern of development. On the right side of this slide, we see evidence from a post-mortem study. 202 00:23:03,990 --> 00:23:14,520 So sometimes scientists have the opportunity to look in more detail at the brain because the next of kin are willing to donate the brain for research. 203 00:23:15,540 --> 00:23:23,790 After tragically, someone with autism this time I'm actually here an observation at the national autism brain back. 204 00:23:25,220 --> 00:23:29,670 But this study comes from California. They have a brain bank for autism, too. 205 00:23:30,450 --> 00:23:35,190 And what they found was that the autistic brain is indeed larger and heavier. 206 00:23:36,710 --> 00:23:42,320 But it's also got 65% more nerve cells or neurones in the frontal cortex. 207 00:23:42,590 --> 00:23:50,870 So again, when you look at the fine detail, so called neuropathology of the brain, you see a difference in the way the brain is structured. 208 00:23:52,190 --> 00:24:01,469 Not a sign of disease, but a sign of difference. It's a bit more evidence and frame difference this time. 209 00:24:01,470 --> 00:24:04,710 We're looking at another structure in the brain, just coloured in green. 210 00:24:05,130 --> 00:24:11,910 It's called the corpus callosum, which is the connective tissue between the two hemispheres, two halves of the brain. 211 00:24:12,250 --> 00:24:18,360 I mean, a portion of this structure is actually smaller in children with autism. 212 00:24:18,360 --> 00:24:23,850 So some bits are larger, some it's a smaller. A whole process of development is different. 213 00:24:27,010 --> 00:24:35,820 This is a very recent study where scientists have worked as a method of looking at connectivity within the brain, 214 00:24:36,330 --> 00:24:44,490 because we imagine that those neural connections in the brain, some of them are long range and some of them are short range. 215 00:24:45,270 --> 00:24:50,310 And there's now a method we have to separate the short range and the long range. 216 00:24:50,520 --> 00:24:57,630 What you find is more of the short range connections in the autistic brain and more of the long range connections in the typical brain. 217 00:24:58,020 --> 00:25:04,740 So again, what we're seeing emerging is that these are individuals with a very different mind, very different brain. 218 00:25:07,690 --> 00:25:09,700 And back to the post mortem studies. 219 00:25:10,510 --> 00:25:17,260 This is about the most detail level that you can get, which is down to the individual neurone or the individual nerve cell. 220 00:25:18,190 --> 00:25:26,140 So now what we're looking at on the right is a neurone from a brain of some doses. 221 00:25:26,410 --> 00:25:31,270 But on the left, the same thing from a typical, typical brain. 222 00:25:32,110 --> 00:25:34,720 What you should be able to see, even with the naked eye, 223 00:25:35,380 --> 00:25:43,500 is that the nerve cell from the person with autism has got more of those white dots up and down the nerve cell. 224 00:25:43,840 --> 00:25:52,830 Each of those white dots is a point of connection between one group and its neighbour, so called dendritic spiders. 225 00:25:53,500 --> 00:26:00,070 And that means that and also some will seeing more connections between nerve cells than in a typical brain. 226 00:26:00,970 --> 00:26:08,950 So far from this being a brain that is in some way disordered or pathological, this is a grey that seems to be developing faster. 227 00:26:09,410 --> 00:26:12,460 It seems to be developing more nerve cells. 228 00:26:12,490 --> 00:26:15,680 It seems to be developing more connections between cells. 229 00:26:16,030 --> 00:26:19,810 And you can just try to imagine what would that do to your experience? 230 00:26:20,200 --> 00:26:23,740 It might mean that you're picking up more information than other people. 231 00:26:24,220 --> 00:26:30,940 So in a lecture theatre like this, if you have autism, you wouldn't necessarily just be focusing on the talk, 232 00:26:30,940 --> 00:26:35,320 but you might be focusing on all kinds of information like the background sounds, 233 00:26:35,620 --> 00:26:42,909 the lights, the patterns of the colours of the seats, as Marcus mentioned, all sorts of things that's just bombarding your senses. 234 00:26:42,910 --> 00:26:47,770 And in some environments that might be overwhelming so-called sensory overload, 235 00:26:48,220 --> 00:26:51,700 but in other environments that might just mean that you're taking in more data, 236 00:26:52,060 --> 00:27:02,500 you're able to see more patterns, more information than the typical brain is some evidence for that sensory hypersensitivity. 237 00:27:03,080 --> 00:27:09,130 So if you ask people with autism to have a brain scan, so now they're not looking at the structure of the brain, 238 00:27:09,370 --> 00:27:18,790 what the function of the brain brain activity and the way this experiment was done just to ask people to wear a blindfold headphones. 239 00:27:19,540 --> 00:27:26,620 And you just look at the brain, see what happens when you play a sound through perhaps through the headphones. 240 00:27:27,010 --> 00:27:31,030 What you find is that in the autistic brain, it's a correct response. 241 00:27:31,240 --> 00:27:38,290 Auditory cortex, just to hear in the sound. So this is evidence of auditory hypersensitivity. 242 00:27:38,830 --> 00:27:49,000 And I think you could do this kind of experiment with the other senses where taste or touch and smell or vision and find a greater response, 243 00:27:49,510 --> 00:27:54,580 so-called sensory hypersensitivity. So when we meet people with autism, we should keep that in mind. 244 00:27:55,180 --> 00:27:58,750 This is a person that might be very sensitive to that requirement. 245 00:27:59,250 --> 00:28:07,030 But we need to make reasonable adjustments to the environments in which they know so that they are autism friendly. 246 00:28:07,540 --> 00:28:12,670 But it might also mean that this is an individual who is picking up much more information than the rest of us. 247 00:28:15,610 --> 00:28:22,989 So I'm a psychologist. And the implication for what I've told you so far is that these individuals, 248 00:28:22,990 --> 00:28:29,380 people with autism, might pick up more detail and maybe less of the big picture. 249 00:28:29,950 --> 00:28:38,230 They might be processing data about what's the evidence for this of here's a test score, added figures test. 250 00:28:38,650 --> 00:28:43,180 Well, you have to find that case as quickly as you can in the overall design. 251 00:28:43,960 --> 00:28:50,770 What we find is that people with autism are super quick, super accurate at spotting the parts within the home. 252 00:28:51,130 --> 00:28:55,390 So their focus of attention is more on the detail and on the big picture. 253 00:28:55,930 --> 00:29:00,640 And again, if you ask them to do that test whilst they're lying in a scanner, having a brand new study, 254 00:29:01,120 --> 00:29:08,800 you find that that passive performance is actually accompanied by less brain activity in the visual cortex. 255 00:29:09,250 --> 00:29:16,440 So the autistic brain is. So carried out on this task, the brain is doing it in the more efficient way. 256 00:29:17,370 --> 00:29:20,910 So although we should think about autism as a disability, 257 00:29:21,630 --> 00:29:32,610 we can design tests which also reveal talent as more evidence for people with autism preferring detail. 258 00:29:33,180 --> 00:29:39,210 I have a big picture. This is actually a test that those of you who are in the field of psychology will recognise. 259 00:29:39,810 --> 00:29:46,580 And it's the block design test which is part of the IQ test of a lot of children and adults are given. 260 00:29:47,310 --> 00:29:54,180 We are asked to do is take the blocks down below and select which ones you need to make the design up about. 261 00:29:54,780 --> 00:30:03,770 Okay, children with autism that adults with autism show their best performance on the subtext of the IQ pressure. 262 00:30:04,890 --> 00:30:14,310 And it's suggested to us because they're very quick at taking apart the big picture and decide projects into its component parts. 263 00:30:14,310 --> 00:30:25,500 They're very quickly looking for the detail, suggesting again that they have a talent for assessing detail over and over the larger context. 264 00:30:27,060 --> 00:30:30,390 I'll show you a few more of these, just to give you a sense of it. 265 00:30:32,070 --> 00:30:37,140 So here the test is simply what lessons you see, and there's no correct answer there. 266 00:30:37,890 --> 00:30:41,400 But people with autism tend to say, I see the latter age group, 267 00:30:42,600 --> 00:30:47,550 people who focus on the big picture might say they see the latter results as a correct. 268 00:30:48,150 --> 00:30:56,850 But really, the test is picking up on whether you preferentially detail or preferentially go for the big picture. 269 00:30:57,330 --> 00:31:04,320 Again, it's a simple test showing that the bias in autism is for the lowest level of detail. 270 00:31:05,190 --> 00:31:14,160 Looking at point pass, this study shows that people with autism are also better. 271 00:31:14,340 --> 00:31:21,720 They score higher on a test of spotting patterns as he presents information across successive slides. 272 00:31:22,170 --> 00:31:29,340 And you see how quickly people can predict where particular information is going to be displayed on the screen. 273 00:31:30,060 --> 00:31:39,960 But people with autism are quicker at picking up these these patterns of how some stimuli, some objects always occur next to or above other ones. 274 00:31:40,360 --> 00:31:45,650 They're very quick. It's impossible patterns. So let's bring this back to life. 275 00:31:46,790 --> 00:31:50,780 This is Derek, the Genie. He has autism. 276 00:31:51,260 --> 00:31:56,890 Some of you may have heard him play it because he plays the piano and he plays publicly. 277 00:31:58,190 --> 00:32:02,510 He's also blind from birth and he has learning difficulties. 278 00:32:02,810 --> 00:32:07,820 In fact, his mental age is something around the equivalent of a three or four year old. 279 00:32:08,720 --> 00:32:13,720 But he only needs to hear any jazz song played once it's been absorbed. 280 00:32:13,790 --> 00:32:24,530 Reproduce it. And he goes around the world on tour performing requests such as numbers that people shout out in the audience, 281 00:32:25,220 --> 00:32:27,980 which is why we've got the piano that just in case is in the audience. 282 00:32:29,300 --> 00:32:38,690 But this is kind of another nice illustration of how the autistic brain and the autistic mind is focusing on persons in his case, 283 00:32:39,020 --> 00:32:43,310 that auditory puzzles he can't see. 284 00:32:43,910 --> 00:32:51,920 But despite that, his brain is latching onto information where there are patterns to be found in the universe. 285 00:32:52,490 --> 00:32:59,330 But he's very quickly changed and his autism is giving rise to his his talent. 286 00:33:01,760 --> 00:33:08,180 So some of you will have come across a book that was published earlier this year, late last year called Mirage Tribes. 287 00:33:09,560 --> 00:33:19,800 It's financial analyst called Steve Silverman and it won the Samuel Jackson Prize for non-fiction for it, 288 00:33:19,820 --> 00:33:28,040 deservedly because it tells a wonderful history of autism about people with autism right through the centuries 289 00:33:28,040 --> 00:33:35,720 who may have not had that formal diagnosis but may have had all the characteristics that you can see. 290 00:33:36,350 --> 00:33:41,150 An image here of Henry Cavendish, the scientist who discovered hydrogen. 291 00:33:42,050 --> 00:33:46,640 Who is somebody in our case, very convincingly, probably had autism. 292 00:33:47,360 --> 00:33:49,520 He did his utmost to avoid people. 293 00:33:50,180 --> 00:33:58,190 He would go in one entrance of the house ensuring that he didn't tell anyone going through the doors that perhaps he was hapless, 294 00:33:58,200 --> 00:34:04,040 really what he was doing, his scientific experiments alone, but he hated social interaction. 295 00:34:04,670 --> 00:34:09,260 Nevertheless, he made remarkable contributions to science. 296 00:34:09,890 --> 00:34:20,270 And those of you who like to eat out, which is the subtitle of Solomon's book, The Legacy of Autism and the Future of Neurodiversity. 297 00:34:21,080 --> 00:34:30,230 His book, one of the reasons why it's done so well, is because it's almost a manifesto for this new concept of neurodiversity. 298 00:34:30,680 --> 00:34:36,850 The idea that there isn't a single way to be normal. There isn't a single way for great people like this. 299 00:34:37,370 --> 00:34:43,430 For me, 100 or even 1000 different ways for the brain to develop that were not so identical. 300 00:34:43,910 --> 00:34:50,660 And you can actually see the image on the front cover of his book is already taken from the more familiar concept of biodiversity. 301 00:34:51,260 --> 00:34:55,850 We don't expect all biological entities to be identical. 302 00:34:56,480 --> 00:35:01,310 That's part of the richness of the forests of the animal kingdom. 303 00:35:02,510 --> 00:35:11,510 And the same way when we think about human brains in any classroom of children or in any audience in a Oxford Playhouse, 304 00:35:11,520 --> 00:35:13,850 we should expect all of these brains to be different. 305 00:35:15,050 --> 00:35:22,940 And this has implications for how we educate, for how we design our environments to maximise human potential. 306 00:35:23,480 --> 00:35:31,040 But it also has the implication that just because someone isn't showing the typical parsnips about evolution, we shouldn't pathologize them. 307 00:35:31,490 --> 00:35:38,570 We should include them. We should make our society more inclusive for people who just think differently. 308 00:35:40,900 --> 00:35:50,050 So this notion of neurodiversity, it's actually been around since about 1998 when it first appeared in print. 309 00:35:51,040 --> 00:35:56,710 The term is actually attributed to a person on the autism spectrum who first coindesk. 310 00:35:57,130 --> 00:35:59,500 You'll increasingly hear people talking about this. 311 00:35:59,950 --> 00:36:07,150 And the reason I think it's so important because for us to say it's a revolutionary concept is it's forcing psychiatry 312 00:36:07,450 --> 00:36:18,760 as a as a profession to rethink the notion of psychiatric illness and to think more about diversity in the population. 313 00:36:19,150 --> 00:36:27,100 Minds differ. This poster is produced by the autism rights movement, 314 00:36:28,450 --> 00:36:35,319 who quite rightly are asking for a difference to be recognised as just as any 315 00:36:35,320 --> 00:36:40,390 minority wants to be recognised as different and to be respected is different. 316 00:36:40,990 --> 00:36:46,390 So we don't expect all fruits to be the same. We shouldn't expect all lines to be the same. 317 00:36:46,990 --> 00:36:52,540 But as they say, which if not less, was inferior, which is different. 318 00:36:53,210 --> 00:36:57,310 They're asking for. You can see this slogan, Autism Acceptance, 319 00:36:57,520 --> 00:37:04,390 which is a very different so of fear to the way the medical profession might previously have thought about autism, 320 00:37:04,780 --> 00:37:14,440 which needed either education, treatment, cure prevention, the very medical model rather than acceptance and support. 321 00:37:17,940 --> 00:37:24,210 This idea about neurodiversity. I think this idea has been around for longer than 1988. 322 00:37:24,780 --> 00:37:31,169 In fact, if you go back to the writings of Albert Einstein, what you see is a nice quotation. 323 00:37:31,170 --> 00:37:38,399 If you judge a fish by its ability to climb a tree, it will lift believing it is stupid as a fish. 324 00:37:38,400 --> 00:37:40,540 A very good clothing, but not very good. 325 00:37:40,560 --> 00:37:49,980 It's another and from which we should take each other, each brain on its own merits, rather than expecting it to be something very different. 326 00:37:51,030 --> 00:37:56,950 TIME People have arcades. I don't think I've had autism, he says. 327 00:37:56,970 --> 00:38:00,360 I do not socialise because it distracts me from my work. 328 00:38:00,960 --> 00:38:09,660 He much prefers the laboratory in physics, theoretical physics, the weather patterns and numbers. 329 00:38:10,380 --> 00:38:17,040 And he liked being alone. He played the violin, but he also liked going sailing. 330 00:38:17,700 --> 00:38:23,440 When he was a Princeton, he used to sail alone. That doesn't mean that there was anything wrong with him. 331 00:38:23,460 --> 00:38:27,660 It just meant that he had a different pattern of interests and he was a bit different. 332 00:38:28,800 --> 00:38:33,840 I would sort of take issue with this idea of trying to diagnose historical figures. 333 00:38:34,170 --> 00:38:36,060 He's not here to speak about itself, 334 00:38:36,780 --> 00:38:47,040 but it is interesting that some of the traits that we associate with autism are found in the biographies of some of these great, talented scientists. 335 00:38:49,340 --> 00:38:53,120 So on the left here, we see the paediatrician, Hans Asperger. 336 00:38:54,290 --> 00:38:59,690 So he's the doctor whose name is not given to one of the subgroups on the autism spectrum. 337 00:39:00,050 --> 00:39:07,520 On the autism spectrum. And a quote from his clinical report, he said, For success in science. 338 00:39:07,790 --> 00:39:09,860 A dash of autism is essential. 339 00:39:10,700 --> 00:39:24,110 But I like this quotation because he is linking on the one hand, something that we think of as a disability, where on the other hand, talent or yes, 340 00:39:24,350 --> 00:39:29,960 talent is also making the age coming up with this idea that you can have a dash of autism, 341 00:39:29,970 --> 00:39:36,290 that it's not that you either have this or you don't have that. But again, I think this was a precursor to the idea of a spectrum. 342 00:39:36,860 --> 00:39:38,600 It runs right through the population. 343 00:39:39,710 --> 00:39:48,800 And I've included here Isaac Newton, again, biographies of Michael Flynn, which have received the diagnosis of autism. 344 00:39:49,400 --> 00:39:57,440 So the discoverer of gravity, who had great difficulties with social relationships throughout his professional career. 345 00:39:58,470 --> 00:40:05,240 And if we focus on his social skills, we might have focussed on areas of difficulty. 346 00:40:05,840 --> 00:40:11,540 But if we actually just focus on what he was good at and we see the positive. 347 00:40:15,030 --> 00:40:23,130 Let's leave that scientists behind because of the difficulty in ever validating the release of the diagnosis. 348 00:40:23,760 --> 00:40:33,600 We've looked at people who have autism, who are living today to see whether they have a scientific interest, if you like. 349 00:40:34,170 --> 00:40:41,610 And one of the ways we've done this is to say give them a questionnaire, asking them how interested they are in systems support, one kind or another. 350 00:40:42,360 --> 00:40:47,430 The systems might be more chemical like a car engine. 351 00:40:48,090 --> 00:40:53,550 They might be electronic like a computer. They might be natural, like the weather. 352 00:40:54,030 --> 00:41:02,669 They might be abstract, like mathematics. And in this questionnaire, we ask individuals with autism, the general population, how interested are you? 353 00:41:02,670 --> 00:41:09,030 Because these very lawful systems that exist out in the world around us and people with autism that 354 00:41:09,030 --> 00:41:16,080 score higher than people without weights in terms of a self-report that they're very interested, 355 00:41:16,680 --> 00:41:23,930 they're drawn to the school systems. So we coined this word systematising. 356 00:41:24,590 --> 00:41:30,170 And I want us to just go into this in a little bit more detail. And I see that there are systems all around us. 357 00:41:30,530 --> 00:41:35,810 And when we systemise, what we're trying to do is identify the laws that come from that system. 358 00:41:36,750 --> 00:41:44,120 It doesn't really matter what the system is, but the process seems to fall into these three steps that you take the inputs. 359 00:41:44,540 --> 00:41:50,240 That's what you see around you. You then observe what happens when an operation occurs. 360 00:41:50,800 --> 00:41:56,380 So some events happens a way, manipulate the process, and then we observe the output. 361 00:41:56,390 --> 00:42:00,830 We see the results of the experiment. And that's really what we call systematising. 362 00:42:01,630 --> 00:42:09,740 And we do that in mathematics. So we might take as the input, the number three, we perform an operation, let's say the key of it. 363 00:42:10,160 --> 00:42:19,910 We get the output, we always get the number 27. So that's a good example, simply a simple example in mathematics that each time you take the inputs, 364 00:42:20,720 --> 00:42:24,170 perform an operation, you should get the identical output. 365 00:42:24,500 --> 00:42:31,550 People with autism seem to like they seem to be fascinated by this kind of predictability we call systemise it. 366 00:42:32,000 --> 00:42:37,520 You can also see a feedback loop because engineers do this when designing systems, 367 00:42:38,120 --> 00:42:43,250 but they're hoping that they're going to get the same result every time when they designed signed a new of engineering. 368 00:42:43,850 --> 00:42:52,760 They're also watching to see what the output is, to see how they can refine that system, to get it to perform, to as perfect a level as possible. 369 00:42:56,000 --> 00:43:04,090 But it turns out that this notion of systemise goes back to the mathematician George. 370 00:43:05,510 --> 00:43:14,850 So in the 19th century, he writes a book called The Laws of Thought, where he was trying to identify what do we do when we're supposed to be rational? 371 00:43:14,870 --> 00:43:19,549 We're trying to use logic. He came up with the idea that the way we think, 372 00:43:19,550 --> 00:43:28,640 the way we draw logical conclusions is what he calls taking something called the if if this is the input. 373 00:43:30,110 --> 00:43:35,690 And he said, we move on to the end and something happens, then we see the result. 374 00:43:36,720 --> 00:43:42,830 But I think this perfectly maps onto the notion of systems inputs, operation outputs. 375 00:43:43,780 --> 00:43:49,969 And George Paul is rightly respected for having created the foundations of the computer age, 376 00:43:49,970 --> 00:43:54,799 because this is exactly what computers do and this is exactly what we see in 377 00:43:54,800 --> 00:44:01,100 the fields of logic in trying to understand what constitutes logical thinking. 378 00:44:01,400 --> 00:44:07,340 Very simple. But there might be circuits in the minds that we're going to just track these relationships, 379 00:44:07,340 --> 00:44:12,470 inputs, operation outputs, or what we'll call if and we'll take. 380 00:44:15,900 --> 00:44:19,020 So here's a very practical example that comes from Vince himself. 381 00:44:19,020 --> 00:44:27,900 He's the co-inventor of the Internet who reports this problem he encountered, which is called the peppercorn problem. 382 00:44:28,350 --> 00:44:35,310 We've all had this where you put the peppercorns into the grinder and sometimes they come out and sometimes they just get stuck. 383 00:44:37,300 --> 00:44:44,140 So if you analyse the problem, which is what he does in terms of this input operation output, 384 00:44:44,680 --> 00:44:50,950 what you can see is if you put the particles in one at a time, as you can see on the left, then you grinds, 385 00:44:51,280 --> 00:44:58,570 you've got a certain outfit, the peppercorn comes out nicely around the if you put lots of peppercorns in at the input, 386 00:44:59,350 --> 00:45:05,500 then you get this constriction kind of bottleneck and you get nothing coming out. 387 00:45:06,280 --> 00:45:15,190 So this is just another simple system that you can analyse in terms of these logical operations, the inputs, the operation and the outfit, 388 00:45:15,730 --> 00:45:23,050 whether it applies to a computer or whether it applies to a household object where you're trying to figure out what on earth is wrong with my pepper, 389 00:45:23,060 --> 00:45:27,280 which isn't. So that's to people with autism. 390 00:45:27,550 --> 00:45:33,370 We've given them little tests of mechanical reasoning of this kind. 391 00:45:33,820 --> 00:45:41,710 We went into secondary schools and came across and we tested children who are in the general population, 392 00:45:42,130 --> 00:45:47,740 which 12 years old, giving them these simple mechanical reasoning problems that they'd never seen before. 393 00:45:48,280 --> 00:45:53,500 And a 12 year old struggling with Asperger's syndrome, despite their disability, 394 00:45:53,710 --> 00:45:58,330 we found that they performed higher, better on this test of mechanical reasoning. 395 00:45:59,020 --> 00:46:03,160 So here the test is that you look at the wheel, this going anti-clockwise, 396 00:46:04,600 --> 00:46:11,140 that's the input you're performing an operation on and you're looking to see if you can predict what people do. 397 00:46:11,500 --> 00:46:17,530 And the answer for those of you who are struggling is that it will be a pattern for the kids with with autism or Asperger's. 398 00:46:17,530 --> 00:46:21,520 Saw this relationship very quickly compared to typical teenagers. 399 00:46:22,000 --> 00:46:28,989 So you might ask, who's got the disability in my university? 400 00:46:28,990 --> 00:46:37,240 We want to see this and little bit more to try to understand this connection between systematic thought and autism. 401 00:46:37,780 --> 00:46:44,860 And we went since the maths department and we simply asked the question to the students, do you have autism? 402 00:46:45,610 --> 00:46:54,760 But you're right. What we found was that there are more students in the maths department with a formal diagnosis of autism in the humanities. 403 00:46:55,450 --> 00:47:03,669 So again, this is showing us that there seems to be a link between minds that are predisposed to looking at patterns, 404 00:47:03,670 --> 00:47:11,170 maybe have a challenge that puzzles, in this case, mathematical patterns and the likelihood of having autism. 405 00:47:14,160 --> 00:47:22,740 We also gave that measured the autistics, the autism spectrum questions, just measuring autistic traits just to remind us, too. 406 00:47:24,360 --> 00:47:28,840 And we gave that to scientists and those working in the humanities. 407 00:47:29,070 --> 00:47:39,510 And what you can see is that even if people in the sciences don't have autism, they just score higher on this measure of autistic traits, 408 00:47:39,510 --> 00:47:44,370 which is a quantitative measure that's distributed throughout the population. 409 00:47:44,790 --> 00:47:50,940 So we're seeing another example of a link between scientific talent and autistic traits. 410 00:47:54,040 --> 00:48:04,930 So you can see how this this scientific ability, what I'm calling system lifesaver, might be adaptive in all sorts of environments. 411 00:48:05,380 --> 00:48:13,120 For example, if you are good at systematising, good at spotting regularities in the world, you can apply it to nature. 412 00:48:13,960 --> 00:48:18,910 You can use that if and when. Logic, if extreme. 413 00:48:19,360 --> 00:48:24,410 And it tastes in this particular way and it might be a problem. 414 00:48:24,670 --> 00:48:34,720 Interest Apple. So you can start classifying nature using this systematising principle and you can do it by looking at the balance all around you. 415 00:48:35,470 --> 00:48:42,580 Again, when you're classifying anything else in nature, using the inputs, operation output logic, 416 00:48:43,480 --> 00:48:55,270 if it's got a blackhead and it's got an orange or the sun, I suppose if it's totally black, I think that it might be appropriate. 417 00:48:55,570 --> 00:48:59,110 So you're looking at nature in this very systematic way, 418 00:48:59,530 --> 00:49:06,730 and we find that people with autism are drawn to this kind of classification of nature, the systematic nature. 419 00:49:09,070 --> 00:49:13,720 So this comes from a website of roses called Sean Locke. 420 00:49:14,650 --> 00:49:18,130 And I would describe him as an autistic capitalist. 421 00:49:18,640 --> 00:49:22,510 He was looking at nature response things that other people receive. 422 00:49:22,550 --> 00:49:32,560 So here he's also looking at the detail and he finds the birds camouflaged against the tree trunk, which is called a little tree creeper. 423 00:49:33,010 --> 00:49:42,040 And he's taking photographs of them. So you can look at his website and see that his way of seeing the world is revealing the beauty of nature. 424 00:49:45,110 --> 00:49:52,690 This is Jacob Barnett, who's in the States, and he's frustrated by mathematics and physics. 425 00:49:53,790 --> 00:49:58,000 As a child, he was precocious in these areas, even though he has autism. 426 00:49:58,540 --> 00:50:04,690 And he was admitted to his university at the age of ten to take a maths and physics course. 427 00:50:05,050 --> 00:50:16,120 So it's a great novel at a precocious age. So again, we're seeing an association between autism and scientific challenge, 428 00:50:16,900 --> 00:50:21,340 where in one context we say he's got a disability that's in the playgrounds. 429 00:50:21,610 --> 00:50:27,100 I'm going to socialise with the other kids, but placed in another context it can really blossom. 430 00:50:29,890 --> 00:50:35,620 He's not the one who came to our clinic. And his passion is gardening. 431 00:50:36,670 --> 00:50:45,670 He got Asperger's syndrome, and he consistently wins the medals at the Chelsea Garden Show for his beautiful confidence. 432 00:50:46,090 --> 00:50:54,340 So he's systemised in nature because he's learned the names and the properties of every plant that you find in Bristol. 433 00:50:54,970 --> 00:51:01,330 But he knows exactly which soil they need to blossom and when they're going to come out at different times of the year. 434 00:51:01,540 --> 00:51:12,220 And you can design the perfect garden. So although he's got a disability, he's also using his very different minds to a fantastic effect. 435 00:51:15,640 --> 00:51:22,540 So we think that there's this link between autism and scientific talent is genetic. 436 00:51:23,110 --> 00:51:31,600 Because if you look at the parents of children with autism or even the grandparents and you look at the occupations that they worked in, 437 00:51:32,230 --> 00:51:36,190 you saw the disproportionate number of works in the field of engineering. 438 00:51:36,940 --> 00:51:42,550 So this is a study just looking at fathers and grandfathers where there's a child with autism in the family. 439 00:51:43,150 --> 00:51:52,000 What we found was that in earlier generations, you don't necessarily see or just when you do see talent in understanding systems, 440 00:51:52,480 --> 00:51:57,550 so did the genetics of scientific or systematising talent. 441 00:51:58,600 --> 00:52:10,750 And the genetics of autism might well be. Just today, a few examples of people who have really made remarkable contributions. 442 00:52:11,710 --> 00:52:15,430 And this is Jim Simons, who is one of the world's richest people. 443 00:52:16,090 --> 00:52:20,590 Something we know from his. He's got one of the largest hedge funds in the world. 444 00:52:21,550 --> 00:52:24,850 He has a child with autism. He's also a mathematician. 445 00:52:24,880 --> 00:52:30,250 And a code cracker is very quick at spotting the patterns in code. 446 00:52:31,210 --> 00:52:38,380 So he's used his remarkable ability to make money and he's giving it back in terms 447 00:52:38,380 --> 00:52:43,840 of philanthropy so that he now funds a lot of autism research internationally. 448 00:52:44,410 --> 00:52:48,700 But again, we're seeing this potentially genetic connection between the parents. 449 00:52:49,330 --> 00:52:54,790 It's mathematically gifted and the existence of a child with autism. 450 00:52:55,900 --> 00:53:00,550 The closer to home. This is Steve Shirley and Stephanie Shirley, 451 00:53:01,750 --> 00:53:11,350 who has donated a lot of money to this university and hospice for the study of mathematics and information technology. 452 00:53:12,010 --> 00:53:14,470 She is a mother with a child with autism. 453 00:53:15,130 --> 00:53:26,110 And in making her well, she's also she wants to give it back to the autism community and particularly in developing services and funding research. 454 00:53:26,470 --> 00:53:35,620 But again, we're seeing this link between the parents who is excellent at Systematising and the likelihood of having a child with autism. 455 00:53:37,900 --> 00:53:45,340 This leads to a prediction Might we expect autism to be more common in places like Silicon Valley, 456 00:53:46,000 --> 00:53:54,640 which attracts people who are talented at systematising, people based because they could use information technology? 457 00:53:55,180 --> 00:54:04,600 Computer science. Just understanding patterns of big data might be fine, but if they settle, then they have children. 458 00:54:06,140 --> 00:54:09,220 We've seen elevated rates of autism in such communities. 459 00:54:10,240 --> 00:54:15,130 Well, we conducted an experiment in a Silicon Valley closer to home. 460 00:54:16,030 --> 00:54:22,480 So this is the map of Holland, the Netherlands, Silicon Valley, a long way away. 461 00:54:22,570 --> 00:54:29,680 We went to Europe because there's a city called Owens Haven, which is the Silicon Valley of the Netherlands. 462 00:54:30,520 --> 00:54:34,570 Eindhoven is interesting because it's got the same type of Institute of Technology. 463 00:54:35,130 --> 00:54:42,370 It's also got the Philips Factory, which has been there for over a hundred years, attracting people who are good at systems. 464 00:54:42,850 --> 00:54:49,900 So we've had several generations of people move into line in settling families. 465 00:54:50,140 --> 00:54:57,580 We can look at the rates of autism amongst their children and we compared that to two other Dutch cities, Utrecht and Holland. 466 00:54:58,180 --> 00:55:01,600 Looking at all the diagnosed cases of autism in these three cities. 467 00:55:02,290 --> 00:55:12,130 The school population. But we can see that autism is more than twice as common in Eindhoven compared to these two other cities. 468 00:55:13,060 --> 00:55:20,110 So this doesn't directly prove the link with parents because all we were doing was looking in the schools. 469 00:55:20,560 --> 00:55:29,380 But it certainly suggests, again, that when you have communities which are enriched for talent and information technology, 470 00:55:30,250 --> 00:55:37,840 we might find higher rates of autism. So I'm going to finish shortly. 471 00:55:38,500 --> 00:55:46,390 I am just trying to bring this together that I've talked a bit about the social difficulties in autism. 472 00:55:46,990 --> 00:55:55,660 And this is a model which is trying to say integrate the social difficulties that you might think of in terms of empathy, 473 00:55:56,020 --> 00:56:03,610 being able to take someone else's perspective, understand what they might be thinking and feeling on one dimension. 474 00:56:04,300 --> 00:56:13,290 So that's the vertical axis, the y axis with another dimension, which is what have been called calling systems. 475 00:56:13,510 --> 00:56:23,560 And the idea is that we all fall somewhere in this space and that these are two directions of personality, if you like. 476 00:56:24,040 --> 00:56:35,590 Some of us have some sort of empathy or better social skills and maybe one less skirt spotting patterns and particularly doing mathematics. 477 00:56:35,980 --> 00:56:44,590 But others might have the opposite profile. So this space is the whole population and what we have been finding in our research. 478 00:56:45,670 --> 00:56:51,070 Let me just help you reach this graph, is that if your 0.0 was in the centre of that graph, 479 00:56:51,460 --> 00:56:56,530 it means you are absolutely average for the population on both dimensions. 480 00:56:57,130 --> 00:57:06,070 And empathy is as good as your system, but you're just kind of in the average on both challenges as you go up. 481 00:57:06,340 --> 00:57:13,570 That vertical axis of empathy is above average and as it goes down, it is below average. 482 00:57:14,180 --> 00:57:18,760 Similarly, on the horizontal axis, as you go out towards the right system. 483 00:57:20,570 --> 00:57:24,520 And as you go over to the left system, rising is below average. 484 00:57:24,970 --> 00:57:27,500 So it could be plotted somewhere in this space. 485 00:57:27,550 --> 00:57:38,840 What we've been finding is that in the white area of the graph of people whose system housing is as good or as bad as their empathy reduction, 486 00:57:38,860 --> 00:57:50,260 a discrepancy between the two. The people up in the light blue areas have higher empathy and systemise, and so they're showing a kind of bias. 487 00:57:50,590 --> 00:57:55,780 We actually find more females in the population but fall into that white blue zone. 488 00:57:57,310 --> 00:58:05,590 In the pink area on the graph are people who share the opposite profile, people whose systematising is at a higher level of empathy. 489 00:58:06,040 --> 00:58:10,060 We find more males in the population fall in that in that sense. 490 00:58:10,900 --> 00:58:20,800 And what we're projecting is that in the red quadrant of this graph, down in the bottom right hand corner, we should find more people with autism. 491 00:58:21,640 --> 00:58:28,690 So in the red zone, your system, I think, might be anywhere from average through to superior. 492 00:58:29,500 --> 00:58:36,250 Your empathy might be below average. So what we find if we actually go out in the population, 493 00:58:36,580 --> 00:58:45,190 give people measures of empathy and systemise it and plot where they fall, or you can see lots of data points. 494 00:58:45,730 --> 00:58:53,410 This is what we have for scientists. So each little blob on the graph is a person and we can see where that takes it. 495 00:58:53,890 --> 00:59:00,600 And you might be able to see that there are more yellow dots up at the top left hand corner. 496 00:59:01,850 --> 00:59:11,210 These are women in the population. More of the green dots in the centre of the graph overhanging the population seems to be a shift. 497 00:59:12,260 --> 00:59:14,180 These are really just about groups. 498 00:59:15,020 --> 00:59:23,180 You can certainly find individuals who are male or female and who are not part of the clout of that group, if you like. 499 00:59:24,050 --> 00:59:28,940 And then we find more of these purple and red dots down at the bottom right hand corner. 500 00:59:29,420 --> 00:59:30,620 Those are people with autism. 501 00:59:31,730 --> 00:59:41,090 So just eyeballing the data, you can see that the population discusses that your gender seems to have something to do with where you might fall, 502 00:59:41,510 --> 00:59:49,370 but actually your gender doesn't predict what kind of mine you're going to have because you might be typical or atypical for your gender. 503 00:59:49,880 --> 00:59:56,120 And if we try and do a count of all those dots that we were just looking at in terms of these different profiles, 504 00:59:56,600 --> 01:00:01,040 what I've tried to pick out to save time, it's just three of these profiles. 505 01:00:01,430 --> 01:00:14,840 So in yellow women whose empathy is higher than their systems that we can see, 43% of women show that profile compared to only 12% of women. 506 01:00:16,250 --> 01:00:18,350 So if we if we look at the of blood, 507 01:00:19,130 --> 01:00:29,630 that's people showing the opposite of that systematising is at a higher level than the empathy that we find is 53% of men and is 21% of women. 508 01:00:30,230 --> 01:00:34,730 So you can see as a group for comparing males and females, we're seeing differences. 509 01:00:35,270 --> 01:00:42,110 Controversially, this is the KISS mentioned, the essential difference, 510 01:00:42,110 --> 01:00:48,319 which is kind of trying to understand some of these groups differences of seeing on average between men and women, 511 01:00:48,320 --> 01:00:54,950 boys and girls in the population, which may have relevance for understanding why autism is more common than boys. 512 01:00:55,700 --> 01:00:59,240 That is that red number at the bottom of this table. 513 01:01:00,590 --> 01:01:08,000 So this is the profile where your systemise is anything from average to above average, but your energy is below average. 514 01:01:08,030 --> 01:01:11,990 So you show a big discrepancy between these two dimensions. 515 01:01:12,540 --> 01:01:16,070 That's where we find about 60% of people with autism. 516 01:01:16,970 --> 01:01:23,880 So the numbers that fit the model perfectly, but the numbers are certainly in the direction predicted by the middle. 517 01:01:25,900 --> 01:01:33,160 So I'm going to finish just by telling you about this child, Marcus Clarke, who is ten years old. 518 01:01:34,030 --> 01:01:37,440 He loves puzzles. He's got autism. 519 01:01:37,510 --> 01:01:43,810 He lives in California. And for him, passing is the Rubik's Cube. 520 01:01:44,770 --> 01:01:53,250 He not only solves the three by three Rubik's Cube very fast, but he can do the four by four, the five by five. 521 01:01:53,260 --> 01:02:00,220 In fact, he relishes it, and he's ranked in the top 100th Rubik's Cube in the world. 522 01:02:01,300 --> 01:02:06,100 So despite just ability, if we saw him socialising with his group, 523 01:02:06,610 --> 01:02:12,830 we also see under the right conditions a fascination, even a talent with passengers. 524 01:02:13,570 --> 01:02:17,620 I'm just talking about him. I would say thank you for your attention. 525 01:02:18,240 --> 01:02:24,010 All right. You said visit our Web site if you want more information about any of the studies that talked about it. 526 01:02:24,430 --> 01:02:27,760 And then we can open it up for questions and discussion. 527 01:02:27,880 --> 01:02:28,680 Thank you very much.