1 00:00:09,770 --> 00:00:15,620 My house. My name is Marcus DeSoto on the Simone professor for the public understanding of science here in all. 2 00:00:16,700 --> 00:00:22,730 Welcome to this icon of Premier events, University of Oxford for engagement in science at the public. 3 00:00:23,000 --> 00:00:26,590 We're bringing back you back to the Playhouse in the newly furnished seats. 4 00:00:26,600 --> 00:00:33,230 I've be trying to work out some patterns of the arrangement I thought I had is completely fox me so I'm probably the best extension of. 5 00:00:35,610 --> 00:00:43,680 But it's great to have such a wonderful audience. I want to thank the Amador Foundation, who financially make this possible as well. 6 00:00:43,980 --> 00:00:49,260 And I think it's a testament to the subjects that we address tonight, 7 00:00:49,260 --> 00:00:54,450 that this property has been the fastest selling celebrity lecture I've been involved in, 8 00:00:54,450 --> 00:01:03,239 because that's the topic that we're going to be talking about is the subject of autism, which affects many people in our society. 9 00:01:03,240 --> 00:01:09,180 But it's maybe I shouldn't say, unfortunately. And that's somehow I think the what we're going to be exploring. 10 00:01:09,180 --> 00:01:16,589 We have a very fantastic speaker, Simon Baron-Cohen, who's the director of the Centre of the Autism Research Centre in Cambridge. 11 00:01:16,590 --> 00:01:27,500 He's Trinity College. Cambridge and I first met him actually because I think a massive audience we often kind of slightly joke about we 12 00:01:28,050 --> 00:01:34,310 there are more of us on the kind of Asperger autistic spectrum than in any other department of its university. 13 00:01:34,320 --> 00:01:40,410 And I do remember an interview a few years ago with one of my colleagues actually when I was in Cambridge, 14 00:01:41,220 --> 00:01:47,310 Richard Dawkins, who and he was being interviewed by Simon Singh in The Guardian. 15 00:01:47,310 --> 00:01:56,320 All three won on Nobel Prize appeals enabled. And he sort of confessed to Simon that, well, I I've on this kind of scale of Asperger's in high school, 16 00:01:56,320 --> 00:02:05,160 I would point out that the six key indicators, which is kind of self-diagnosed himself and Simon picked this up and one of his books, 17 00:02:05,160 --> 00:02:12,450 which I really enjoyed reading The Essential Difference Exploring what makes an autistic brain slightly different. 18 00:02:12,450 --> 00:02:20,220 What is the Defining Factor? Actually dedicated a chapter to exploring whether Richard was in fact Asperger's or not. 19 00:02:20,820 --> 00:02:28,500 And that's really at the heart of the talk today, because we're going to be exploring the question of autism and minds, what the science. 20 00:02:28,500 --> 00:02:32,940 So, you know, is it's actually a positive trait for us mathematicians. 21 00:02:33,540 --> 00:02:45,220 We just have a great welcome to Simon Baron-Cohen. Thank you very much. 22 00:02:45,240 --> 00:02:47,190 It's a great pleasure to be back in Oxford. 23 00:02:47,700 --> 00:02:56,220 I was a student here some 30 years ago, so there's a nostalgia about getting off the train and coming back into this beautiful city. 24 00:02:57,510 --> 00:03:01,710 And I want to thank the organisers of this lecture. 25 00:03:02,190 --> 00:03:05,580 You're inviting me to give a talk in this series? 26 00:03:06,420 --> 00:03:10,319 It feels like I have an honour this afternoon. 27 00:03:10,320 --> 00:03:15,090 This evening. I'll be exploring this topic of autism. 28 00:03:15,570 --> 00:03:19,140 But its connection to scientific talent. 29 00:03:23,860 --> 00:03:31,510 So I thought I'd start just with an image of almost a stereotype of a child with autism. 30 00:03:32,350 --> 00:03:38,740 Because sometimes a picture says more than words can. So what we see is a boy. 31 00:03:39,070 --> 00:03:42,190 And autism affects boys much more often than girls. 32 00:03:43,090 --> 00:03:53,560 And this boy is playing alone. And part of the diagnosis of autism are difficulties in social interaction and in communication. 33 00:03:54,490 --> 00:03:59,350 But you can also see in this picture that he's doing something intelligent. 34 00:03:59,800 --> 00:04:04,600 He's lining up his toys in a very precise way, but he's making consonants. 35 00:04:05,380 --> 00:04:15,880 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. 36 00:04:16,420 --> 00:04:21,280 And what upsets me most is if someone comes along and disturbs that perfect order. 37 00:04:22,210 --> 00:04:29,950 But either way, what we're seeing is in some respects a disability struggling with socialisation. 38 00:04:30,370 --> 00:04:34,390 But in other respects, a mind that is very precise and very ordered. 39 00:04:36,860 --> 00:04:39,200 Here's one more child with autism. 40 00:04:40,730 --> 00:04:52,100 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. 41 00:04:52,760 --> 00:04:57,470 So again, we're seeing a child who in one context struggles. 42 00:04:58,150 --> 00:05:05,080 We shouldn't lose sight of the disability. But left to their own devices, they have a fascination with patterns. 43 00:05:05,480 --> 00:05:13,030 And that's really the topic I want to discuss. Before I do that, a little bit about the background to autism, 44 00:05:13,540 --> 00:05:22,390 because this graph shows you that autism has been diagnosed increasingly, often year by year. 45 00:05:22,750 --> 00:05:27,100 The data here goes from 1996 through to 2005. 46 00:05:27,430 --> 00:05:31,660 Just showing you the number of cases per thousand being diagnosed. 47 00:05:31,690 --> 00:05:36,220 So there's been a steady increase. But some people have wondered what's driving this. 48 00:05:37,030 --> 00:05:40,540 And in all likelihood, it's quite ordinary factors. 49 00:05:40,810 --> 00:05:46,750 We're just getting more aware of autism, but we're getting better at recognising it. 50 00:05:47,710 --> 00:05:55,120 There are more services on the ground looking for it, but also we've broadened our definition of autism, 51 00:05:55,510 --> 00:05:58,960 particularly to include a subgroup called Asperger's Syndrome. 52 00:05:59,290 --> 00:06:05,560 But Mark has just referred to. So we've added another subgroup and that will, of course inflate the numbers. 53 00:06:07,060 --> 00:06:17,710 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. 54 00:06:17,890 --> 00:06:24,190 So you might be wondering, where is this leading autism is being diagnosed more and more. 55 00:06:24,840 --> 00:06:33,400 I think this is a good thing because the diagnosis, when it's done properly, is done for a reason, which is to help individuals who are struggling. 56 00:06:34,630 --> 00:06:39,400 So I think we're getting closer to recognising all of the individuals that need that support. 57 00:06:40,120 --> 00:06:49,659 I don't think we're over diagnosing. But I suppose the other trends that comes out from these two problems is that in the old days, 58 00:06:49,660 --> 00:06:54,970 and this is when I started doing autism research, the condition was thought to be very rare. 59 00:06:55,900 --> 00:06:58,540 They used to say four in 10,000 children. 60 00:06:59,020 --> 00:07:09,700 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 00:07:10,270 --> 00:07:13,420 The Americans regard this as a disease or a disorder. 62 00:07:14,410 --> 00:07:23,410 But you can see that the current figures are one in 48 points and one in 189 girls. 63 00:07:23,890 --> 00:07:26,890 So we're still seeing autism being more common in boys. 64 00:07:27,580 --> 00:07:31,960 If you average across the ten genders, comes out to one in 68. 65 00:07:32,500 --> 00:07:35,500 So it's no longer rare. It's actually very common. 66 00:07:36,940 --> 00:07:47,620 And the graph, in a way, shows you autism in a snapshot, because it also shows you that some people on the autism spectrum, 67 00:07:47,620 --> 00:07:53,560 as it's called, also have learning difficulties that delay in the development more generally. 68 00:07:54,220 --> 00:07:59,050 They may even have language delay. And that's true both in the boys and the girls. 69 00:07:59,200 --> 00:08:02,830 There's a proportion who have learning difficulties as well. 70 00:08:03,190 --> 00:08:09,070 But you can have autism without any learning difficulties, without any delay in your development. 71 00:08:09,640 --> 00:08:12,760 So average IQ, even above average IQ. 72 00:08:13,090 --> 00:08:16,630 And that's really what creates this breadth of the spectrum. 73 00:08:18,810 --> 00:08:27,420 So when this term, the autism spectrum was coined, goes back to 1988, we thought this was very interesting, 74 00:08:27,420 --> 00:08:33,330 the idea that there might be a spectrum of autistic traits and thoughts about how we could measure it. 75 00:08:34,620 --> 00:08:40,680 So Mark has just mentioned this questionnaire that Rich Apportions has taken and completed. 76 00:08:42,180 --> 00:08:46,470 It's called the Autism Spectrum Question. So you can find it on the Web. 77 00:08:46,920 --> 00:08:53,970 You can complete it and see how many autistic traits you have on the front line. 78 00:08:54,500 --> 00:09:02,010 On the left bell curve shows that autistic traits are normally distributed throughout the population. 79 00:09:02,190 --> 00:09:10,319 We all have some. So there's a bell curve at the sideline on the right of schools that people who 80 00:09:10,320 --> 00:09:14,640 end up with the diagnosis shape the distribution of schools that they have. 81 00:09:15,120 --> 00:09:18,900 And again, even within the clinic, you see a range of scores. 82 00:09:19,260 --> 00:09:25,740 I should help you to read this by saying that along the horizontal axis, the x axis, it goes from zero 3 to 50. 83 00:09:26,640 --> 00:09:33,150 And if you're scoring very high so you're shifted over towards the right of that graph, you may need a diagnosis. 84 00:09:33,510 --> 00:09:43,860 But it's only when these traits interfering with your ability to cope in life, whether as a child or as an adult, that you would need a diagnosis. 85 00:09:44,100 --> 00:09:50,220 Otherwise, these traits are just there and they might have some adaptive or positive characteristics. 86 00:09:52,410 --> 00:09:57,570 So what else do we know about autism? Well, the first thing is we know that it's partly genetic. 87 00:09:58,410 --> 00:10:04,740 So here we put an image of a family where one of the children has autism. 88 00:10:05,430 --> 00:10:08,880 What we know is that if one child in the family has autism, 89 00:10:09,390 --> 00:10:15,630 the likelihood of another child in the same family also receiving a diagnosis is one in three. 90 00:10:16,920 --> 00:10:23,970 So although in the general population it's about 1%, it's as soon as you've got a family relative with the diagnosis, 91 00:10:24,450 --> 00:10:29,490 your odds of getting of getting diagnosed dramatically shapes up. 92 00:10:29,970 --> 00:10:32,310 And we think that that's to do with genetics. 93 00:10:34,170 --> 00:10:45,780 Reason We think that these days you can look at the genome and the picture on the top pair shows you the human chromosomes, 23 pairs of chromosomes. 94 00:10:47,040 --> 00:10:55,290 But each little dots on the chromosomes is a genetic association that's been reported in the scientific literature. 95 00:10:56,490 --> 00:11:02,760 This is being constantly updated on the website that is shining down to a gender Safa age old. 96 00:11:03,510 --> 00:11:14,550 Because almost every week in one of the scientific journals, there'll be a new report about a genetic discovering genes associated with autism. 97 00:11:14,910 --> 00:11:20,040 When I last spoke, there were over 400 genes that have been identified as linked to autism. 98 00:11:20,520 --> 00:11:25,200 So we know we're talking about a complex condition in terms of it being polygenic. 99 00:11:26,340 --> 00:11:34,200 And we know that these genes are literally found right across the genome, every human chromosome. 100 00:11:35,460 --> 00:11:38,340 You can see that a lot of these genes are expressed in the brain. 101 00:11:38,670 --> 00:11:48,700 So this this image superimposes gene expression amongst some of those genes that have been identified as linked to autism. 102 00:11:48,700 --> 00:11:57,450 And those ones that are found in the brain that can be published in our high profile journals and in the scientific world. 103 00:11:58,980 --> 00:12:08,100 So I'm going to assume that autism is partly genetic. Not completely genetic, because you can have identical twins like these sisters. 104 00:12:08,740 --> 00:12:16,620 One has autism and one doesn't. So the very existence of so-called discordant pairs of twins, 105 00:12:17,490 --> 00:12:23,760 even though they're genetically identical but one has a11, doesn't mean that genes can't be the whole story. 106 00:12:24,210 --> 00:12:29,130 There must be environmental factors that interact with your genetic predisposition. 107 00:12:30,300 --> 00:12:34,020 We don't have such a good handle on what those genetic factors are. 108 00:12:34,710 --> 00:12:39,270 But suffice it to say that twin studies just make it. 109 00:12:39,660 --> 00:12:44,760 They make the argument that environment must also be interacting with genetics. 110 00:12:47,440 --> 00:12:52,150 So I've mentioned that autism entails disability. I don't want to lose sight of that. 111 00:12:53,200 --> 00:12:58,750 But when you have your diagnosis, it's because you really need it if you are struggling. 112 00:12:58,990 --> 00:13:05,020 And universities like Oxford have students with autism who hopefully find their 113 00:13:05,020 --> 00:13:10,450 way to the disability business and get extra support because of that disability. 114 00:13:10,960 --> 00:13:14,590 And that disability is very much in the realm of social interaction. 115 00:13:15,160 --> 00:13:21,640 What we know is that there's difficulties or differences in ability to cope with the social world. 116 00:13:21,910 --> 00:13:30,040 Start very early. This is a study looking at brain activity in babies where there's already a child with autism. 117 00:13:30,370 --> 00:13:35,500 So that tracking the next child in the family has a genetic risk for autism. 118 00:13:36,460 --> 00:13:42,550 And just looking at whether they showed the expected pattern of brain activity when they're looking at a face 119 00:13:42,880 --> 00:13:50,920 or the eyes either directed straight at the child or looking away from the child in a typical child's way, 120 00:13:50,920 --> 00:13:56,920 operating at the child's brain is exquisitely sensitive to whether they're being looked at or not being looked at. 121 00:13:57,100 --> 00:13:59,020 We pay a lot of attention to faces, 122 00:13:59,590 --> 00:14:09,790 but we find that in children with autism or children who have a risk of autism for genetic reasons, that brain activity is different. 123 00:14:09,790 --> 00:14:15,850 It's reduced in response to changes in looking at someone else's gaze. 124 00:14:16,870 --> 00:14:20,860 So that's very early on, even as young as six months old. 125 00:14:23,200 --> 00:14:29,290 This study comes from California University of California at San Diego, where they took children. 126 00:14:29,800 --> 00:14:33,760 At the earliest point, you can diagnose autism, which is about two years old, 127 00:14:34,750 --> 00:14:41,560 and they presented children coming into the clinic either with a human face to the past or a geometric design. 128 00:14:42,490 --> 00:14:51,670 And they simply measured how long the child looks at either the social stimulus, the human face, or the non-social stimulus, the geometric design. 129 00:14:52,390 --> 00:14:59,080 What they found is that if a child looks for more than 70% of the time, the non-Social Social stimulus, 130 00:14:59,080 --> 00:15:04,540 the geometric design, the probability that that child has autism was 100%. 131 00:15:05,560 --> 00:15:14,890 So I when I read this of film, I was quite impressed that there might be a behavioural test that could be used to diagnose autism. 132 00:15:15,580 --> 00:15:18,880 So there's a little caveat here before I go into that. 133 00:15:20,050 --> 00:15:25,959 I suppose what we're seeing is that the typical child can pay a lot of attention to faces. 134 00:15:25,960 --> 00:15:35,560 The faces are important, but these kids who go on to develop autistic or receive a diagnosis of autism may be less interested in faces, 135 00:15:35,920 --> 00:15:41,560 more interested in patterns. But what's the caveats about this diagnostic test? 136 00:15:41,900 --> 00:15:48,820 Well, if you drill down into the data, you actually see each of these dots is a child. 137 00:15:49,360 --> 00:15:54,490 And they've been assigned into different groups on the autism graph of the red dots. 138 00:15:55,510 --> 00:16:02,980 And the horizontal line going across the screen shows you if you're looking more at the geometric patterns rather than faces, 139 00:16:03,400 --> 00:16:06,970 if you're above that line, you're looking 70% of the time. 140 00:16:07,520 --> 00:16:13,060 That's geometric design. So you can see it's true. There's a lot more of those red dots above the line. 141 00:16:13,840 --> 00:16:18,370 So a lot of children with autism would get picked up using this behavioural test. 142 00:16:18,730 --> 00:16:24,670 But equally those mathematicians or those who love statistics in the audience, 143 00:16:25,060 --> 00:16:34,390 we'll see that there's a wide range and it's a lot of kids who the red dots below the line, which means that they'd be missed by this test. 144 00:16:34,870 --> 00:16:38,980 So just to interpret some of these scientific findings with caution, 145 00:16:39,370 --> 00:16:45,580 but either way it's telling us that as a group, children with autism seem to be more biased. 146 00:16:45,670 --> 00:16:55,780 So the thing that passes is that they are not faces. This is a study that came from Yale University where they used instructions. 147 00:16:56,650 --> 00:17:02,200 So this time what they're doing is putting the child in front of a computer whilst they're watching a movie, 148 00:17:02,710 --> 00:17:07,450 and the computer can track what the person is looking at once they're watching the movie. 149 00:17:07,990 --> 00:17:17,410 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 00:17:18,070 --> 00:17:27,180 The yellow person is where the typical viewer is watching or looking, mostly looking at the eye region of the face, the red area, 151 00:17:27,180 --> 00:17:34,870 and seeing this image is where people with autism tend to look less at the eyes and more at the mouth whilst they're watching the movie. 152 00:17:35,320 --> 00:17:40,090 So again, we're seeing differences in how people with autism look at faces. 153 00:17:40,690 --> 00:17:49,970 They may not be showing the typical profile is the typical person of attention when they're presented with sensory information. 154 00:17:53,960 --> 00:18:03,500 So if we took a kind of developmental approach to thinking about children, child development and social understanding, 155 00:18:04,550 --> 00:18:10,700 if you're not looking so much faces and if you're not really thinking about people as much as a typical child, 156 00:18:11,150 --> 00:18:16,250 that might mean that your delays in development, that what's called theory of mind, 157 00:18:16,250 --> 00:18:19,970 is being able to imagine what other people are thinking or feeling. 158 00:18:20,510 --> 00:18:25,010 You have to put yourself into someone else's shoes and take someone else's perspective. 159 00:18:25,520 --> 00:18:27,320 And that's exactly what's found in autism. 160 00:18:28,190 --> 00:18:37,819 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 00:18:37,820 --> 00:18:45,350 where there's an element of deception in which the typical child loves to engage in things that leave the child with autism, 162 00:18:45,350 --> 00:18:53,060 often feeling confused, stressed, and they prefer just to withdraw into the more predictable realms of patterns. 163 00:18:56,420 --> 00:18:58,520 We tried to track what's going on in the brain, 164 00:18:59,600 --> 00:19:06,980 which is different in autism compared to a typical person when they're asked to look at the eye region of the face. 165 00:19:07,730 --> 00:19:08,390 So up above, 166 00:19:08,480 --> 00:19:17,870 we showed people photographs of the eye region and we asked them to pick which of these four was best described for the person in the photo, 167 00:19:18,080 --> 00:19:22,760 just thinking or feeling. So this is a tough test. 168 00:19:22,760 --> 00:19:28,310 All you've got is the eyes. The correct answer here is that she's a bit dispirited or a bit sad. 169 00:19:29,000 --> 00:19:32,300 I can see some of you nodding, suggesting that you've got that one right. 170 00:19:34,820 --> 00:19:39,260 It's tough because all four words describe possible states of mind. 171 00:19:39,800 --> 00:19:43,640 It's tough because the black and white photo is not very high resolution. 172 00:19:44,600 --> 00:19:48,920 It's tough because you've only got the fragments of information that have the whole facial expression. 173 00:19:49,730 --> 00:19:54,530 What you can see on the graph is that people with autism still no on this test. 174 00:19:55,550 --> 00:20:02,480 There's the two parts, the males and females over to the left of that graph compared to typical males and females. 175 00:20:02,850 --> 00:20:06,650 This was quite a large dataset because we collected the data online. 176 00:20:07,280 --> 00:20:12,559 When we asked people to tell you that test was there lying in a scanner for a brain scan so we 177 00:20:12,560 --> 00:20:19,010 can look at patterns of brain activity and we also see a difference in the typical population. 178 00:20:19,370 --> 00:20:25,160 We see a lot of activity in a part of the frontal lobe, the left inferior function gyrus, 179 00:20:25,550 --> 00:20:31,910 and we find reduced activity in the autistic brain when they're looking at these facial expressions, 180 00:20:31,910 --> 00:20:36,140 just the eyes to try and decode what someone else is thinking or feeling. 181 00:20:37,130 --> 00:20:40,250 So that's showing some of the disability in autism. 182 00:20:42,620 --> 00:20:53,230 What we're also aware of is that when we look at the brain in autism, we don't see evidence that things are broken or disorders or dysfunctional. 183 00:20:53,590 --> 00:21:02,260 We actually simply see difference. The autistic brain is just developing differently, and this is a field that I want to build on. 184 00:21:03,280 --> 00:21:08,470 So I'm going to show you some of these differences as part of the journey into understanding autism. 185 00:21:10,270 --> 00:21:14,890 So this study is looking at one particular structure in the brain, the amygdala. 186 00:21:15,280 --> 00:21:19,570 Some people think of the amygdala as the emotional centre of the brain. 187 00:21:20,740 --> 00:21:29,350 It's deep in the brain, below the cortex. And this structure is larger in children with autism compared to typical children. 188 00:21:30,160 --> 00:21:34,600 So what we're seeing is a difference in the volume of a particular region of the brain. 189 00:21:35,110 --> 00:21:38,500 It's not a sign that anything is dysfunctional or disease. 190 00:21:39,080 --> 00:21:45,550 And this is why we should start challenging the perception or the label that autism is a disorder. 191 00:21:45,850 --> 00:21:57,420 Because what we're seeing is difference. It's a bit more evidence for the idea that autism entails just a different pattern of brain development. 192 00:21:59,130 --> 00:22:11,130 So the graph on the left is where each child is a child and they have two brain scans during that during that transition. 193 00:22:11,790 --> 00:22:17,940 So what that means is you can track how the brain is growing. You're looking at brain development or brain growth. 194 00:22:18,330 --> 00:22:27,840 You can join the dots to see if the typical grade shown in blue or the autism green zone in red differ in terms of where the brain is growing. 195 00:22:28,380 --> 00:22:35,040 What you can see is that there is a data difference. So this is just showing the total amount of grey matter in the brain. 196 00:22:35,400 --> 00:22:39,030 So again, just looking at this, that's an aspect of the volume of the brain. 197 00:22:39,840 --> 00:22:45,120 And that's this is quite early in development during the first five years of life. 198 00:22:45,630 --> 00:22:51,870 The autistic brain is larger at each of those timepoints than the typical brain on average. 199 00:22:52,350 --> 00:22:59,020 So the brain in autism seems to be growing faster and larger than in typical toddlers. 200 00:23:00,930 --> 00:23:06,240 Again, not a sign of disease or pathology. Simply a different pattern of development. 201 00:23:07,350 --> 00:23:11,220 On the right side of this slide, we see evidence from a post-mortem study. 202 00:23:11,880 --> 00:23:22,380 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 00:23:23,370 --> 00:23:31,190 After tragically, someone with autism this time I'm actually here in Oxford is the national autism brain. 204 00:23:33,160 --> 00:23:37,530 This study comes from California. I have a brain bank for autism, too. 205 00:23:38,310 --> 00:23:43,020 And what they found was that the autistic brain is indeed larger and heavier, 206 00:23:44,580 --> 00:23:50,160 but it's also got 65% more nerve cells of neurones in the frontal cortex. 207 00:23:50,460 --> 00:23:58,680 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 00:24:00,060 --> 00:24:07,340 Not a sign of disease, but a sign of difference. There's a visual evidence of brain difference. 209 00:24:08,930 --> 00:24:12,590 This time we're looking at another structure in the brain, just coloured in green. 210 00:24:13,010 --> 00:24:17,840 It's called the corpus callosum, which is the connective tissue between the two hemispheres. 211 00:24:18,620 --> 00:24:26,190 Two halves of the brain. And a portion of this structure is actually smaller than children with autism. 212 00:24:26,210 --> 00:24:31,700 So some bits are larger, some of which are smaller. A whole pattern of development is different. 213 00:24:34,860 --> 00:24:43,650 This is a very recent study where scientists have worked as a method of looking at connectivity within the brain, 214 00:24:44,190 --> 00:24:52,350 because we imagine that those neural connections in the brain and some of them are long range and some of them are short range, 215 00:24:53,130 --> 00:24:58,140 and there's now methods to be able to separate the short range and the long range. 216 00:24:58,380 --> 00:25:05,430 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 00:25:05,880 --> 00:25:12,600 So again, what we're seeing emerging is that these are individuals with a very different mind mindset, a very different brain. 218 00:25:15,580 --> 00:25:21,100 Getting back to the post mortem studies, this is about the most detailed level that you can get, 219 00:25:21,400 --> 00:25:25,150 which is down to the individual neurone or the individual nerve cell. 220 00:25:26,050 --> 00:25:35,020 So now what we're looking at on the right is a neurone from a brain of someone with autism on the left. 221 00:25:35,800 --> 00:25:39,120 The same thing from a typical person. Typical brain. 222 00:25:39,970 --> 00:25:42,580 What you should be able to see, even with the naked eye, 223 00:25:43,240 --> 00:25:51,400 is that the nerve cell from the person with autism has got more of those white dots up and down the nerve cell. 224 00:25:51,730 --> 00:26:00,690 Each of those white zones is a points of connection between one meal and its neighbour, so called dendritic spines. 225 00:26:01,300 --> 00:26:07,930 And what that means is that in autism we're seeing more connections between nerve cells than in a typical brain. 226 00:26:08,830 --> 00:26:16,840 So far from this being a brain that is in some way disordered or pathological, this is a brain that seems to be developing faster. 227 00:26:17,210 --> 00:26:20,330 It seems to be developing more nerve cells. 228 00:26:20,350 --> 00:26:23,560 It seems to be developing more connections between nerve cells. 229 00:26:23,920 --> 00:26:27,670 And you could just try to imagine what would that do to your experience? 230 00:26:28,060 --> 00:26:31,600 It might mean that you're picking up more information than other people. 231 00:26:32,110 --> 00:26:38,790 So in a lecture theatre like this, if you have autism, you wouldn't necessarily just be focusing on the talk, 232 00:26:38,800 --> 00:26:43,180 but you might be focusing on all kinds of information like the background sounds, 233 00:26:43,480 --> 00:26:50,770 the lights, the patterns of the colours of the seats, as Mark has mentioned, all sorts of things that's just bombarding your senses. 234 00:26:50,770 --> 00:26:53,140 And in some environments that might be overwhelming. 235 00:26:53,950 --> 00:26:59,560 So full sensory overload, but in other environments that might just mean that you're taking in more data, 236 00:26:59,920 --> 00:27:10,330 you're able to see more patterns, more information than the typical brain is some evidence for that sensory hypersensitivity. 237 00:27:11,040 --> 00:27:19,600 If you ask people with autism to have a brain scan now, they're not looking at the structure of the brain or the function of the brain brain activity. 238 00:27:20,290 --> 00:27:28,449 And the way this experiment was done, just to ask people to wear blindfolds where headphones and you just look at 239 00:27:28,450 --> 00:27:33,210 the brain and see what happens when you play the sounds through the headset, 240 00:27:33,550 --> 00:27:41,920 through the headphones. What you find is that in the autistic brain is a greater response to the auditory cortex just to hear in the sound. 241 00:27:42,580 --> 00:27:46,180 So this is evidence of auditory hypersensitivity. 242 00:27:46,690 --> 00:27:49,959 And I think you could do this kind of experiment with the other senses, 243 00:27:49,960 --> 00:27:59,590 with taste or touch or smell or vision and find a greater response, so-called sensory hypersensitivity. 244 00:27:59,950 --> 00:28:06,610 So when we meet people with autism, we should keep that in mind. This is a person that might be very sensitive to their environment, 245 00:28:07,090 --> 00:28:14,890 but we need to make reasonable adjustments to the environments in which they learn so that they are autism friendly. 246 00:28:15,400 --> 00:28:20,530 But it might also mean that this is an individual who's picking up much more information than the rest of us. 247 00:28:23,480 --> 00:28:30,830 So I'm a psychologist. And the implication for what I've told you so far is that these individuals, 248 00:28:30,830 --> 00:28:37,280 people with autism, might pick up more detail and maybe less of the big picture. 249 00:28:37,820 --> 00:28:41,900 They might be processing data. What's the evidence for this? 250 00:28:42,320 --> 00:28:50,990 Well, here's a test. It's called the embedded figures test, where you have to find that as quickly as you can in the overall design. 251 00:28:51,680 --> 00:28:58,610 And what we find is that people with autism are super quick, super accurate at spotting the parts within the home. 252 00:28:59,000 --> 00:29:03,230 So their focus of attention is more on the detail than on the big picture. 253 00:29:03,840 --> 00:29:08,450 And again, if you ask them to do that test whilst they're lying in a scanner, having a brain scan, 254 00:29:08,990 --> 00:29:16,610 it finds that that passive performance is actually accompanied by last spring activity in the visual cortex. 255 00:29:17,120 --> 00:29:24,290 So the autistic brain is superior on this task, but the brain is doing it in a more efficient way. 256 00:29:25,250 --> 00:29:32,780 So although we should think about autism as a disability, we can design tests which also reveal talents. 257 00:29:35,440 --> 00:29:40,450 Here's more evidence for people with autism prefer in detail. 258 00:29:41,020 --> 00:29:47,040 I have a big picture. This is actually a test that those of you who are in the field of psychology will recognise. 259 00:29:48,040 --> 00:29:56,139 It's the block design test, which is part of the IQ test for a lot of children and adults we are asked to do is 260 00:29:56,140 --> 00:30:02,020 take the blocks down below and select which ones you need to make the design up about. 261 00:30:02,650 --> 00:30:11,680 Again, children with autism and the adults with autism show their best performance on the subtests of the IQ measure. 262 00:30:12,730 --> 00:30:17,680 And it's suggested that that's because they're very quick at taking apart the big 263 00:30:17,680 --> 00:30:24,070 picture and decipher into its component parts very quickly looking for detail, 264 00:30:25,330 --> 00:30:33,340 suggesting again that they have a talent at processing detail over and over the larger context. 265 00:30:34,930 --> 00:30:38,260 I'll show you a few more of these, just to give you a sense of it. 266 00:30:39,940 --> 00:30:45,000 So here the test is simply what message you see. And there's no characters they have. 267 00:30:45,730 --> 00:30:49,240 But people with autism tend to say, I see the latter age group, 268 00:30:50,350 --> 00:30:55,390 people who focus on the big picture might say they see the latter and both answers are correct. 269 00:30:56,020 --> 00:31:04,750 But really, the test is picking up on whether you preferentially detail or preferentially go for the big picture. 270 00:31:05,200 --> 00:31:12,190 Again, it's a simple test showing that the bias in autism is for the lowest level of detail. 271 00:31:13,060 --> 00:31:17,420 Looking at what kind of pass, I didn't say. 272 00:31:17,450 --> 00:31:21,940 This study shows that people with autism are also better. 273 00:31:22,210 --> 00:31:29,580 They score higher on a test of spotting patterns as he presents information across successive slides. 274 00:31:30,040 --> 00:31:39,620 And you see how quickly people can predict where particular information is going to be displayed on the screen for people with autism are quicker. 275 00:31:39,640 --> 00:31:47,800 Picking up these these patterns of how some stimulate some objects always occur next to or above other ones. 276 00:31:48,220 --> 00:31:53,510 They're very quick assessments of a person's. So let's bring this back to life. 277 00:31:54,680 --> 00:31:58,640 This is Derek. The power of a genie. He has autism. 278 00:31:59,120 --> 00:32:04,760 Some of you may have heard him play it because he plays the piano and he plays publicly. 279 00:32:05,840 --> 00:32:10,370 And he's also blind from birth. And he has learning difficulties. 280 00:32:10,700 --> 00:32:15,680 In fact, his mental age is something around the equivalent of a three or four year old. 281 00:32:16,580 --> 00:32:22,160 But he only needs to hear any jazz song played once it's been reproduced. 282 00:32:23,900 --> 00:32:32,390 And he goes around the world on tour, performing requests of jazz numbers that people shout out in the audience. 283 00:32:33,110 --> 00:32:35,840 Which is why we've got the piano here, just in case is in the audience. 284 00:32:37,160 --> 00:32:46,550 But this is kind of another nice illustration of how the autistic brain and the autistic mind is focusing on persons in his case, 285 00:32:46,910 --> 00:32:51,230 that auditory puzzles he can't see. 286 00:32:51,770 --> 00:32:59,780 But despite that, his brain is latching on to information where there are patterns to be found in the universe. 287 00:33:00,350 --> 00:33:07,180 But he's very quick, intricate, and his autism is giving rise to his his talent. 288 00:33:09,640 --> 00:33:16,000 So some of you will have come across the book that was published earlier this year, late last year called Nero Triumphs. 289 00:33:16,720 --> 00:33:19,900 And it's by a journalist, Steve Silverman. 290 00:33:21,430 --> 00:33:28,420 And it won the Samuel Jackson Prize for non-fiction, very deservedly, 291 00:33:28,810 --> 00:33:35,889 because it tells a wonderful history of autism about people with autism right through the centuries 292 00:33:35,890 --> 00:33:43,620 who may have not had that formal diagnosis and may have had all the characteristics that you can see. 293 00:33:44,230 --> 00:33:54,430 An image here of Henry Cavendish, the scientist who discovered hydrogen, who Silberman argues very convincingly, probably had autism. 294 00:33:55,210 --> 00:33:57,400 He did his utmost to avoid people. 295 00:33:58,060 --> 00:34:04,960 He would go in one entrance of the house, ensuring that he didn't tell anyone going through any of the other doors at the house. 296 00:34:05,320 --> 00:34:11,890 He was happiest really when he was doing his scientific experiments alone, but he hated social interaction. 297 00:34:12,520 --> 00:34:17,110 Nevertheless, he made remarkable contributions to science. 298 00:34:17,800 --> 00:34:28,120 Now, those of you who, like James, helped with the subtitle of Solomon's book, The Legacy of Autism and the Future of Neurodiversity. 299 00:34:28,930 --> 00:34:38,080 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. 300 00:34:38,530 --> 00:34:41,260 The idea that there isn't a single way to be normal. 301 00:34:41,860 --> 00:34:48,490 There isn't a single way that the brain is probably 100 or even a thousand different ways for the brain to develop. 302 00:34:49,870 --> 00:34:54,340 But we're not all identical. And you can actually see the image on the front cover of his book. 303 00:34:55,030 --> 00:34:58,480 He's really taken from the more familiar concept of biodiversity. 304 00:34:59,140 --> 00:35:03,730 We don't expect all biological entities to be identical. 305 00:35:04,360 --> 00:35:09,160 That's part of the richness of the forests and of the animal kingdom. 306 00:35:10,360 --> 00:35:19,389 And in the same way, when we think about human brains in any classroom of children or in any audience in a Oxford Playhouse, 307 00:35:19,390 --> 00:35:21,730 we should expect all of these brains to be different. 308 00:35:22,900 --> 00:35:30,790 And this has implications for how we educate, for how we design our environments to maximise human potential. 309 00:35:31,330 --> 00:35:38,890 But it also has the implication that just because someone isn't showing their typical personal development, we shouldn't pathologize them. 310 00:35:39,370 --> 00:35:46,420 We should include them. We should make our society more inclusive for people who just think differently. 311 00:35:48,760 --> 00:35:58,030 So this notion of neurodiversity, it's actually been around since about 1998 when it first appeared in print. 312 00:35:58,900 --> 00:36:04,540 The term is actually attributed to a person on the autism spectrum who first coindesk. 313 00:36:05,020 --> 00:36:07,420 You'll increasingly hear people talking about autism. 314 00:36:07,810 --> 00:36:16,060 And the reason I think it's because for us to say it's a revolutionary concept is it's forcing psychiatry as a as 315 00:36:16,060 --> 00:36:26,620 a profession to rethink the notion of a psychiatric illness and to think more about diversity in the population. 316 00:36:26,770 --> 00:36:30,970 Our mind is different. And indeed, 317 00:36:31,160 --> 00:36:40,370 this poster is produced by the autism rights activists who quite rightly are asking for that difference to 318 00:36:40,370 --> 00:36:48,230 be recognised as just as any minority wants to be recognised and different and to be respected is different. 319 00:36:48,860 --> 00:36:54,230 So we don't expect all fruits to be the same. We shouldn't expect the lines to be the same. 320 00:36:54,860 --> 00:37:02,150 But as they say, we're different, but we're not. This was inferior, which is different, and they're asking for. 321 00:37:02,720 --> 00:37:05,150 You can see that in autism acceptance, 322 00:37:05,390 --> 00:37:12,230 which is a very different social fear to the way the medical profession might previously have thought about autism, 323 00:37:12,650 --> 00:37:22,310 which needed either eradication in treatment, cure prevention, the very medical model, rather than acceptance and support. 324 00:37:25,580 --> 00:37:32,080 The signs are about neurodiversity. I think this idea has been around for longer than 1988. 325 00:37:32,620 --> 00:37:39,040 In fact, if you go back to the writings of Albert Einstein, what you see is a nice quotation. 326 00:37:39,040 --> 00:37:46,269 If you judge a fish by its ability to climb a tree, it will lift believing it is stupid as a fish. 327 00:37:46,270 --> 00:37:48,970 A very good one. Very, very good. That's another. 328 00:37:49,750 --> 00:37:57,820 And probably wish we should take each animal, each brained on its own merits rather than expecting it to be something very different. 329 00:37:58,450 --> 00:38:02,560 And Einstein and people have argued they also have had autism. 330 00:38:03,880 --> 00:38:08,200 He says, I do not socialise because it would distract me from my work. 331 00:38:08,830 --> 00:38:20,410 He much prefers the laboratory in physics, theoretical physics, but it happens in numbers and he liked being alone. 332 00:38:21,790 --> 00:38:24,880 He played the violin, but he also liked going sailing. 333 00:38:25,540 --> 00:38:31,300 When he was in Princeton, he used to sail alone. That doesn't mean that there was anything wrong with him. 334 00:38:31,330 --> 00:38:35,530 It just meant that he had a different parcel of interests and he was a bit different. 335 00:38:36,700 --> 00:38:41,680 I would sort of take issue with this idea of trying to diagnose historical figures. 336 00:38:42,040 --> 00:38:43,900 He's not here to himself. 337 00:38:44,650 --> 00:38:54,600 But it is interesting that some of the traits that we associate with autism are found in the biographies of some of these very talented scientists. 338 00:38:57,210 --> 00:39:00,990 So on the left here, we see the paediatrician, Hans Asperger. 339 00:39:02,160 --> 00:39:07,530 So he's the doctor whose name is now given to one of the subgroups on the autism spectrum. 340 00:39:07,890 --> 00:39:15,390 On the autism spectrum. And a quote from his clinical record, he said, For success in science. 341 00:39:15,660 --> 00:39:22,260 A dash of autism is essential. So I quite like his position because he's linking, on the one hand, 342 00:39:22,860 --> 00:39:32,640 something that we think of as disability with, on the other hand, talents or yes, talent. 343 00:39:33,810 --> 00:39:37,799 He's also making this idea of coming up with this idea that you can have a dash of autism, 344 00:39:37,800 --> 00:39:40,360 that it's not that you either have this or you don't have it. 345 00:39:40,440 --> 00:39:46,440 But again, I think this was a precursor to the idea of a spectrum that runs right through the population. 346 00:39:47,580 --> 00:39:56,640 And I've included here Isaac Newton, who are kind of biographies of Michael Flynn, would have received a diagnosis of autism. 347 00:39:57,270 --> 00:40:05,280 So the discoverer of gravity. But again, he had great difficulties with social relationships throughout his professional career. 348 00:40:06,400 --> 00:40:13,110 And if we focus on his social skills, we might have focussed on areas of difficulty. 349 00:40:13,710 --> 00:40:19,380 But if we actually just focus on what he was good at and we see the positive. 350 00:40:22,880 --> 00:40:31,010 Let's leave that scientists behind because of the difficulty in ever validating why they needed a diagnosis. 351 00:40:31,610 --> 00:40:41,450 We've looked at people who have autism, who are living today to see whether they have a scientific interest, if you like. 352 00:40:42,020 --> 00:40:49,460 And one of the ways we've done this is to give them a questionnaire, asking them how interested they are in systems of one kind or another. 353 00:40:50,280 --> 00:40:55,280 The systems might be mechanical like a car engine. 354 00:40:55,970 --> 00:41:01,400 They might be electronic like a computer. They might be natural, like the weather. 355 00:41:01,910 --> 00:41:08,600 They might be abstract, like mathematics. And in this questionnaire, we ask individuals with autism, the general population, 356 00:41:09,410 --> 00:41:15,379 How interested are you in these very lawful systems that exist out in the world 357 00:41:15,380 --> 00:41:19,790 around us and people with autism that score higher than people without faces? 358 00:41:19,790 --> 00:41:27,050 And in terms of a self-report that they're very interested, they're drawn to lawful systems. 359 00:41:29,750 --> 00:41:35,030 So we coined this word Systematising, and I want us to just go into this in a little bit more detail. 360 00:41:35,560 --> 00:41:43,700 The idea that there are systems all around us. And when we systemise, what we're trying to do is identify the laws that govern that system. 361 00:41:44,600 --> 00:41:52,010 It doesn't really matter what the system is, but the process seems to fall into these three steps that you take the inputs. 362 00:41:52,400 --> 00:41:58,100 That's what you see around you. You then observe what happens when an operation occurs. 363 00:41:58,650 --> 00:42:04,040 So some events happen as a way of manipulating the person, and then you observe the outcome. 364 00:42:04,250 --> 00:42:08,650 We see the results. And that's really what we call systematising. 365 00:42:09,710 --> 00:42:14,480 And we do that in mathematics. So we might take as the input for number three. 366 00:42:14,960 --> 00:42:20,750 We perform an operation. Let's say we cube it, we get the output, we always get the number 27. 367 00:42:21,860 --> 00:42:27,770 So there's a good example, simply a simple example in mathematics that each time you take the inputs, 368 00:42:28,580 --> 00:42:32,120 perform an operation, you should get the identical output. 369 00:42:32,210 --> 00:42:39,410 And people with autism seem to like they seem to be fascinated by this kind of predictability we call systemise it. 370 00:42:39,860 --> 00:42:45,370 You can also see a feedback because engineers do this when they're designing systems, 371 00:42:45,940 --> 00:42:51,110 but they're hoping that they're going to get the same result every time when they design the new route of engineering. 372 00:42:51,790 --> 00:43:00,620 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. 373 00:43:03,870 --> 00:43:12,600 And it turns out that this notion of systemise goes back to the mathematician George Poole. 374 00:43:13,380 --> 00:43:22,740 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 trying to be rational, 375 00:43:22,740 --> 00:43:27,420 we're trying to use logic. And he came up with the idea that the way we think, 376 00:43:27,420 --> 00:43:36,510 the way we draw logical conclusions is what he calls taking something called the if if this is the inputs. 377 00:43:37,950 --> 00:43:41,760 And he said, we move on to the end and something happens. 378 00:43:42,390 --> 00:43:50,700 Then we see the results. And I think this perfectly maps onto the notion of systemise inputs, operation outputs. 379 00:43:51,630 --> 00:43:57,840 And George Poole is rightly respected for having created the foundations of the computer age, 380 00:43:57,840 --> 00:44:02,669 because this is exactly what computers do and this is exactly what we do in 381 00:44:02,670 --> 00:44:08,970 the field of logic in trying to understand what constitutes logical thinking. 382 00:44:09,270 --> 00:44:10,020 Very simple. 383 00:44:10,650 --> 00:44:19,760 But there might be circuits in the minds that we're going to just track these relationships, inputs, operation outputs, or what we will call if and. 384 00:44:23,770 --> 00:44:26,860 So here's a very practical example that comes from Vince himself. 385 00:44:26,860 --> 00:44:35,770 He's the co-inventor of the Internet, but who reports this problem that he encountered, which is called the peppercorn problem. 386 00:44:36,190 --> 00:44:43,150 We've all had this where you put the peppercorns into the grinder and sometimes they come out and sometimes they just get stuck. 387 00:44:45,160 --> 00:44:52,000 So if you analyse the problem, which is what he does in terms of this input operation output, 388 00:44:52,540 --> 00:44:55,510 what you can see is if you put the peppercorns in one at a time, 389 00:44:55,990 --> 00:45:03,310 as you can see on the left, when you grind, you've got a certain outfit, the peppercorn comes out nicely around. 390 00:45:04,030 --> 00:45:13,360 If you put lots of peppercorns in at the input, then you get this constriction kind of bottleneck and you get nothing coming out. 391 00:45:14,170 --> 00:45:23,020 So this is just another simple system that you can analyse in terms of these logical operations the inputs, the operation and the output, 392 00:45:23,590 --> 00:45:27,430 whether it applies to a computer or whether it applies to a household object 393 00:45:27,940 --> 00:45:35,080 where you're trying to figure out what on earth is wrong with black pepper. So that's for people with autism. 394 00:45:35,410 --> 00:45:41,230 We've given them little tests of mechanical reasoning of this kind. 395 00:45:41,710 --> 00:45:49,570 We went into secondary schools and came back and we tested children who are in the general population, 396 00:45:49,990 --> 00:45:55,600 which obviously was giving them these little mechanical reasoning problems that they'd never seen before. 397 00:45:56,140 --> 00:46:01,360 And then 12 year olds, children with Asperger's syndrome and despite their disability, 398 00:46:01,600 --> 00:46:06,190 we found that they performed higher, better on this test of mechanical reasoning. 399 00:46:06,910 --> 00:46:11,010 So here the test is that you look at the real this going anti-clockwise. 400 00:46:12,460 --> 00:46:19,000 That's the person you're performing an operation on it and you're looking to see if you can predict what people do. 401 00:46:19,360 --> 00:46:23,170 And the answer for those of you who are struggling is that it will move back and forth. 402 00:46:23,530 --> 00:46:29,380 The kids with with autism or Asperger's saw this relationship very quickly compared to typical teenagers. 403 00:46:29,860 --> 00:46:32,140 So you might ask, who's got a disability? 404 00:46:35,770 --> 00:46:45,190 So in my university, we wanted to pursue this a little bit more to try and understand this connection between systematic thought and autism. 405 00:46:45,640 --> 00:46:54,050 And we went since the maths department and we simply asked the question to the students, do you have autism or do right? 406 00:46:54,970 --> 00:47:02,590 What we found was that there are more students in the maths department with a formal diagnosis of autism than in the humanities. 407 00:47:03,310 --> 00:47:11,530 So again, this is showing us that there seems to be a link between minds that are predisposed to looking at passages, 408 00:47:11,530 --> 00:47:19,000 maybe at a challenge that passes in this case, like most passages and the likelihood of having an autism. 409 00:47:22,010 --> 00:47:30,410 We also gave that measure the autistic to the autism spectrum questions just measuring autistic traits to see if this is one of those. 410 00:47:32,240 --> 00:47:36,710 And we gave that to scientists and those working in the humanities. 411 00:47:36,730 --> 00:47:41,930 And again, what you can see is that even if people in the sciences don't have autism, 412 00:47:41,930 --> 00:47:52,250 they just score higher on this measure of autistic traits, which is a quantitative measure that's distributed throughout the population. 413 00:47:52,640 --> 00:47:58,790 So we're seeing another example of a link between scientific talent and autistic traits. 414 00:48:01,910 --> 00:48:12,770 So you can see how this this scientific ability, what I'm calling Systematising, might be adaptive in all sorts of environments. 415 00:48:13,250 --> 00:48:19,070 For example, if you're good at Systematising, you're good at spotting regularities in the world. 416 00:48:19,670 --> 00:48:33,320 You can apply it to nature. You can use that if and then logic if extreme and it tests in this particular way, then it might be a delicious novel. 417 00:48:33,830 --> 00:48:42,560 So you can start classifying nature using this systematising principle, and you can do it by looking at the balance all around you. 418 00:48:43,360 --> 00:48:50,420 Again, when you're classifying anything else in nature, you're using the inputs operation output logic. 419 00:48:51,590 --> 00:48:58,730 If it's called a black and it's got an orange body, then it's all finished. 420 00:48:59,090 --> 00:49:03,100 If it's totally black, then it might be a black point. 421 00:49:03,440 --> 00:49:06,950 So you're looking at nature in this very systematic way, 422 00:49:07,400 --> 00:49:14,600 and we find that people with autism are drawn to this kind of classification of nature as systematising nature. 423 00:49:16,940 --> 00:49:21,540 So this comes from the websites of a young man with autism called Sean Locke. 424 00:49:23,480 --> 00:49:30,350 I would describe him as an autistic capitalist. He loves looking at nature, response things that other people miss. 425 00:49:30,440 --> 00:49:40,430 So here he's also looking at the detail and he finds the birds camouflaged against the tree trunk, which is called the Little Tree Creeper. 426 00:49:40,910 --> 00:49:49,880 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. 427 00:49:52,980 --> 00:50:00,560 This is Jake, the Polymath. He's in the States and he's frustrated by mathematics and physics. 428 00:50:01,680 --> 00:50:05,840 As a child, he was precocious in these areas, even though he has autism. 429 00:50:06,410 --> 00:50:12,560 And he was admitted to his university at the age of ten to take a maths and physics course. 430 00:50:12,920 --> 00:50:15,440 Such a great level at a precocious age. 431 00:50:16,250 --> 00:50:28,010 So again, we're seeing some association between autism and scientific challenge, where in one context you say he's got a disability, 432 00:50:28,090 --> 00:50:34,970 passing the playgrounds, having to socialise with the other kids, but placed in another context it can really blossom. 433 00:50:37,850 --> 00:50:43,490 He's not the one who came to our clinic. And his passion is gardening. 434 00:50:44,540 --> 00:50:53,540 He's got Asperger's syndrome. And he consistently wins medals at the Chelsea Garden shed for his beautiful carpets. 435 00:50:53,970 --> 00:51:02,180 So he's systemised in nature because he's learnt the names and the properties of every plant that you find in Britain, 436 00:51:02,790 --> 00:51:09,170 and he knows exactly which soil they need to blossom in, when they're going to come out at different times of the year. 437 00:51:09,410 --> 00:51:20,090 And he can design the perfect garden. So although he's got a disability, he's also using his very different mind to a fantastic effect. 438 00:51:23,530 --> 00:51:30,370 So we think that there's this link between autism and scientific talent is genetic. 439 00:51:30,970 --> 00:51:39,400 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, 440 00:51:40,120 --> 00:51:44,020 you saw the disproportionate number of them worked in the field of engineering. 441 00:51:44,830 --> 00:51:50,410 So this is a study just looking at fathers and grandfathers where there's a child with autism in the family. 442 00:51:51,010 --> 00:51:59,830 What we found was that in earlier generations, you don't necessarily see autism, but you do see challenges in understanding systems. 443 00:52:00,340 --> 00:52:05,450 So did the genetics of scientific or systemise intelligence. 444 00:52:06,460 --> 00:52:18,590 And the genetics of autism might well be. I'll just say a few examples of people who have really made remarkable contributions. 445 00:52:19,580 --> 00:52:23,270 And this is Jim Simons, who is one of the world's richest people. 446 00:52:23,960 --> 00:52:28,460 Some of you know him and he's a he's got one of the largest hedge funds in the world. 447 00:52:29,420 --> 00:52:34,430 He has a child with autism. He's also a mathematician and a coach cracker. 448 00:52:35,450 --> 00:52:46,219 He's very quick spotting the patterns in code. So he's used his remarkable ability to make money and he's giving it back in terms 449 00:52:46,220 --> 00:52:51,680 of philanthropy so that he now funds a lot of autism research internationally. 450 00:52:52,280 --> 00:52:56,540 But again, we're seeing this potentially genetic connection between the parents. 451 00:52:57,200 --> 00:53:02,660 He's mathematically gifted and the existence of a child with autism. 452 00:53:03,770 --> 00:53:08,390 And closer to home, this is Steve, Shirley James, Stephanie Shirley, 453 00:53:09,620 --> 00:53:19,220 who has donated a lot of money to this university at Oxford for the study of mathematics and information technology. 454 00:53:19,880 --> 00:53:22,220 She is a mother with a child with autism. 455 00:53:23,000 --> 00:53:33,950 And in making her well, she's also she wants to give it back to the autism community, particularly in developing services and funding research. 456 00:53:34,310 --> 00:53:43,460 But again, we're seeing this link between a parent who is excellent at Systematising and the likelihood of having a child with autism. 457 00:53:45,580 --> 00:53:56,320 So this leads to a prediction. Might we expect autism to be more commonly in places like Silicon Valley, which attracts people who are talented? 458 00:53:56,650 --> 00:54:07,360 At Systematising, people move because they could use information technology, computer science, just understanding patterns and big data. 459 00:54:09,100 --> 00:54:17,080 What we find is that if they sample that, perhaps they will see elevated rates of autism in such communities. 460 00:54:18,100 --> 00:54:22,900 Well, we conducted an experiment in Silicon Valley closer to home. 461 00:54:23,890 --> 00:54:30,340 So this is the map of the Netherlands, Silicon Valley, a long way away. 462 00:54:30,510 --> 00:54:37,540 We went to Europe because there's a city called Eindhoven, which is the Silicon Valley of the Netherlands. 463 00:54:38,380 --> 00:54:44,680 Eindhoven is interesting because it's called the Eindhoven Institute of Technology, and it's also about the Philips factory, 464 00:54:45,270 --> 00:54:50,230 which has been there for over 100 years, attracting people here with goods and systems. 465 00:54:50,740 --> 00:54:55,900 So we've had several generations of people moving to wine tasting, settling, 466 00:54:56,860 --> 00:55:00,610 having families, and we can look at the rates of autism amongst their children. 467 00:55:01,030 --> 00:55:09,430 And we compared that to two other Dutch. This is Utrecht and Holland, looking at all the diagnosed cases of autism in these three cities. 468 00:55:09,850 --> 00:55:19,990 What's the school population? But what we can say is that autism is more than twice as common in 87 compared to these two other cities. 469 00:55:20,950 --> 00:55:27,940 So this doesn't directly prove the link with parents because all in all, we were say it's looking in the schools. 470 00:55:28,450 --> 00:55:37,240 But it certainly suggests, again, that when you have communities which are enriched for television and information technology, 471 00:55:38,110 --> 00:55:45,700 we might find higher rates of autism. So I'm going to finish shortly. 472 00:55:46,360 --> 00:55:54,250 I just trying to bring this together that I've talked a bit about the social difficulties in autism. 473 00:55:54,880 --> 00:56:03,550 And this is a model which is trying to integrate the social difficulties that you might think of in terms of empathy, 474 00:56:03,880 --> 00:56:11,470 being able to take someone else's perspective, understand what they might be thinking and feeling on one dimension. 475 00:56:12,160 --> 00:56:21,280 So that's the vertical axis, the y axis with another dimension, which is what I've been calling systems that. 476 00:56:23,190 --> 00:56:31,410 The idea is that we all fall somewhere in this space and that these are two dimensions of the personality, if you like. 477 00:56:31,920 --> 00:56:43,440 Some of us have sort of better empathy or better social skills, and maybe we're less good at spotting patterns and particularly doing mathematics. 478 00:56:43,860 --> 00:56:52,440 But others might have the opposite profile. So this space is the whole population and what we have been finding in our research. 479 00:56:53,550 --> 00:56:55,290 Let me just help you raise this graph. 480 00:56:55,560 --> 00:57:04,380 If you're at 0.0 was in the centre of that graph, it means your absolute the average for the population on both dimensions. 481 00:57:05,020 --> 00:57:08,790 Empathy is as good as your system. 482 00:57:09,240 --> 00:57:16,350 You're just kind of in the average of Congress I mentioned as you go up that vertical axis, 483 00:57:16,650 --> 00:57:21,420 your empathy is above average and as you go down, empathy is below average. 484 00:57:22,020 --> 00:57:29,940 Similarly, on the horizontal axis, as you go up towards the right, you'll systemise coverage as you go over to the left. 485 00:57:30,240 --> 00:57:35,370 The system, I think, is below average, so everybody could be plotted somewhere in this space. 486 00:57:35,850 --> 00:57:45,780 Finally, is that in the white area of the graph are people whose system systematising is as good or as bad as their empathy. 487 00:57:46,170 --> 00:57:57,479 They don't show a discrepancy between the two. The people up in the light blue areas have higher empathy than the systems and especially the kind 488 00:57:57,480 --> 00:58:03,600 of bias we actually find more females in the population that fall into that white blue zone. 489 00:58:05,190 --> 00:58:13,470 In the pink area on the graph are people who share the opposite profile, people whose systematising is at a higher level of empathy. 490 00:58:13,920 --> 00:58:17,940 We find more males of the population fall in that in that sense. 491 00:58:18,760 --> 00:58:28,620 And what we're projecting is that in the right quadrant of this graph, down in the bottom right hand corner, we should find more people with autism. 492 00:58:29,520 --> 00:58:39,630 So in the red zone system, Isaac might be anywhere from average three to superior, but your empathy might be below average. 493 00:58:40,680 --> 00:58:44,010 So what we find, if we actually go out in the population, 494 00:58:44,430 --> 00:58:53,040 give people measures of empathy and systemise it and plot where they fall, or you can see lots of data points. 495 00:58:53,580 --> 00:59:01,260 This is what we love for scientists. So each little blob on the graph is a person and we can see where they're located. 496 00:59:01,740 --> 00:59:08,460 And you might be able to see that there are more yellow dots up at the top left hand corner. 497 00:59:09,720 --> 00:59:17,280 These are women in the population, more of the green dots in the centre of the graph and the remainder of the population. 498 00:59:17,750 --> 00:59:22,020 It seems to be a shift, but these are really just about groups. 499 00:59:22,890 --> 00:59:31,050 You can certainly find individuals who are male or female in terms of who are not part of the cloud with that group, if you like. 500 00:59:31,890 --> 00:59:36,840 And then we find more of these purple and red dots down at the bottom right hand corner. 501 00:59:37,230 --> 00:59:38,460 And those are people with autism. 502 00:59:39,600 --> 00:59:48,930 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, 503 00:59:49,380 --> 00:59:57,240 but actually your gender doesn't predict what kind of mine have because you might be typical or atypical for your gender. 504 00:59:57,750 --> 01:00:03,960 And if we try to account of all those dots that we were just looking at in terms of these different profiles, 505 01:00:04,470 --> 01:00:08,910 what I've tried to pick out to save time is just three of these profiles. 506 01:00:09,300 --> 01:00:22,680 So in yellow and women whose empathy is higher than their system, we can see 43% of women show that profile compared to only 12% of men. 507 01:00:24,120 --> 01:00:29,080 So if we if we look at the blue number, that's kind of the opposite of that. 508 01:00:29,100 --> 01:00:37,500 Systematising is at a higher level than the empathy that we find, 53% of men versus 21% of women. 509 01:00:38,100 --> 01:00:42,570 So you can see as a group for comparing males and females, we're seeing differences. 510 01:00:43,140 --> 01:00:49,950 Controversially, this is the book that Mark is mentioned called The Essential Difference, 511 01:00:49,950 --> 01:00:56,159 which is kind of trying to understand some of these group differences we're seeing on average between men and women, 512 01:00:56,160 --> 01:01:03,780 boys and girls in the population, which may have relevance for understanding why autism is more common in boys and girls, 513 01:01:03,780 --> 01:01:07,110 that right now we're at the bottom of this table. 514 01:01:08,490 --> 01:01:11,670 So this is the profile where your systematising is. 515 01:01:11,670 --> 01:01:15,880 Anything from average to above average for your average is below average. 516 01:01:15,900 --> 01:01:19,830 So you show a big discrepancy between these two dimensions. 517 01:01:20,370 --> 01:01:23,900 And that's where we find. About 60% of people with autism. 518 01:01:24,860 --> 01:01:28,070 So the numbers don't fit the model perfectly. 519 01:01:28,460 --> 01:01:31,770 But the numbers are certainly in the direction predicted by the middle. 520 01:01:33,770 --> 01:01:37,070 So I'm going to finish just by telling you about this child. 521 01:01:38,070 --> 01:01:43,100 That's Paul, who is ten years old. He loves puzzles. 522 01:01:44,330 --> 01:01:51,560 He's got autism. He lives in California. And for him, he passes through that kid. 523 01:01:52,640 --> 01:02:02,180 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, in fact, he relishes. 524 01:02:03,680 --> 01:02:08,060 And he's ranked in the top 100 Rubik's Cube in the world. 525 01:02:09,160 --> 01:02:11,500 So just so it's just ability. 526 01:02:11,800 --> 01:02:22,360 If we saw him socialising with his group, we also see under the right conditions a fascination, even a talent with passengers on the stock van. 527 01:02:22,840 --> 01:02:28,030 I would say thank you for your attention and invite you to visit our website if you want more 528 01:02:28,030 --> 01:02:35,590 information about any others I've talked about and then we can open it up for questions and discussion. 529 01:02:35,740 --> 01:02:36,490 Thank you very much.