Welcome to day five of Brugmas today. I'm going to be talking about back rooms level 56 a.k.a Frostbite this level is perfect for Christmas time because it's freezing cold here. Yeah, that's the only reason it's perfect I guess thank you for watching and let's get into it Shall we Brugley merges out to click the top link in the description to grab some cool merch if you get some You're guaranteed to be sent to the back rooms So back rooms level 56 is very dangerous Of course it is but it's classified as a class 5e difficulty Which means that it's unsafe and unsecure and the climate itself is very dangerous The level is actually made up of a cave system That's made up of rocks and ice the actual cave layout is kind of a circle swirl type shape That leads to a larger center area It's a pretty simple concept the closer you get to this center area the colder and more dangerous it gets the ice here On the cave is smooth and it's all a light blue color There's actually a light coming from an unknown source that shines behind it So the light will then get diffused by the ice and then it'll cause there to be a bluish glow on the floor cave And on this floor cave is where most of the rocks and puddles are and everything here is just rocky and wet and cold When you first spawn inside the level you'll start in the outer section Which is of course at the very beginning of the swirl This is the part that you'll likely survive pretty easily because it stays around 32 degrees Fahrenheit or freezing But it can get so unimaginably cold the deeper you go in that the lowest it's ever been is recorded to be negative 459 degrees Fahrenheit and it's in those sections or stuff could get real dangerous if you're not careful The most dangerous thing for humans here is frost bite Because the level just gets colder and colder as you get deeper into it And you won't really realize how freezing you are until you're a human popsicle Things like heat lamps and stuff have been tested to see if they work and anything that gets over 150 degrees just stops working and it won't ever work again It just turns itself off and doesn't turn back on another strange quirk of the level is that there's a bunch of Elements in their liquid form on the ground here things like nitrogen helium oxygen and even liquid Hydrogen have been found dripping from the ceilings and walls and puddling up on the floor obviously It's not really good to get these chemicals on your body or to breathe them in But since this level is drippy wet and closed in you have no other choice But to be exposed to them But whatever you do do not drink the liquid in the puddles on the floor because it's not water my friend It's chemicals. There are these old looking rinky dinky crates that have been found in the level that seem to have some kind of supplies in them It looks like people left them here when they were trying to explore the level But they had to leave quickly and so they just decided not to pick them up on the way out Sometimes in the crates there could be a cold suit or two or sometimes it could be food or supplies or weapons that kind of deal Which leads some people to believe that other groups of people or creatures have attempted to explore this level But it had to quickly leave. What do you think comment below your theories on that? Like I've said this whole video the closer you get to the center part of the level the colder it gets and when you do start Getting closer the ice will start to compact and get smoother and instead of the floor being rocky and soily It'll start to be completely like an ice rink the ceiling of the cave will have these huge bumpy icicles and sharp icicles At some spots above you and these icicles have fallen before and you definitely don't want to be under them Since you don't want to get impaled by one But when you're walking make sure you look up to see that there's nothing above you now Also, no one knows what's actually close to the center of the level since you literally Instantly freeze if you tried to go with no gear But someone did get pretty close to the center and they said the air itself Started to freeze like all the liquid. It's there freezes instantaneously in the air Which means it would be pretty hard to breathe but the very core of the level has a large open circular room and this room has been Nicknamed the singularity supposedly only a handful of people have even seen the singularity and lived to tell the tale And they got here by using a huge puffer jacket thing that they found in a supply crate Now the roof in this singularity is pretty strange because there's holes in it And it lets some kind of light in and it makes the entire room weirdly lit It starts the room is like a vacuum in a way because it's absolute zero here like there's no temperature It's just so cold that it's absolute zero, but who knows I wouldn't want to figure out the entities in this level are actually pretty rare And they can be found in the cave and if you are seeing one You're gonna see one pretty far out in the caves death rats and death moths are pretty common as well But each of them have a thick white fur on them instead of the usual brown color So they must have adapted to this cold environment There's also a pretty strange spider entity that lives in the center singularity of the level There's no information about it But people have seen it slowly and creepily crawling on the ceiling above it before okay to enter the level you can No clip into a cold part of level eights cave or you can walk into a cavern on level 93 to be sent here and exit you have to find a noticeably wide part of the cave That leads off into a more snowy calm tunnel and then walk through that to get to level 57 Which I'll be going over in tomorrow's episode. So stay tuned That's it for the video. Thank you so much for watching until the end I love and appreciate each and every one of you and I cannot believe how amazing you all are Hope you'll have a great winter break and getting ready for Christmas if you celebrate Christmas is literally right around the corner I hope you all are excited check below for the merch link if you want to grab some brugly clothing This drop is amazing really think y'all will like this tag me on Twitter if you get some because I will follow everybody I see the tags me. I'm really excited to continue to drop more brugly merch next year. This is the first one of many Thank you so much for your support. Thank you so much for everything and I'll see you in the next video tomorrow For day 6 of brugmas. Peace


Dr. Judith Rappaport. Nurses are in the business of nurturing. And we look to our psychologist, scientist, friends to teach us about the population who we will care for. I am so delighted to be able to introduce Dr. Judith Rappaport, who comes to this year's Nobel conference from Washington, DC, where she and her husband live and practice she maintains the privileged life of full-time researchers at the National Institutes of Health. Here, too, they've raised two very successful sons and are going on to be grandparents and improve the race. Born and raised in New York City, she recalls her own childhood as a delightful one where she could go out to play in Central Park and walk home from school with complete safety. Her parents made sure that she was given every opportunity to visit the many museums in New York and even took her to the theater on a monthly basis. So a wonderful beginning. And then she went on to Swarthmore, where she was, again, feeling privileged to attend the many seminars and discussions which propelled her on to the magna cum laude, which she received there, and went on to Harvard Medical School, where she received her degree and did her clinical and research training at Massachusetts Mental Health Center in Boston, Children's Hospital in Washington, DC, and the Laboratory of Psychology at the National Institute of Mental Health in Bethesda, Maryland. Judith learned the Swedish language and found it to be an asset when she was doing her two-year fellowship in Sweden at both the Psychology Institute of Uppsala and the Karolinska Hospital in Stockholm. Since 1984, she has been the chief of the Child Psychiatry Branch, National Institute of Mental Health. In addition to her research at NIMH, she is also professor of psychiatry at George Washington University School of Medicine and clinical professor of psychiatry and pediatrics at Georgetown University Medical School. A past president of the American Psychopathological Association and a fellow of the American Academy of Arts and Sciences, she has served on many editorial boards and national advisory committees, including the Society for Research on Child and Adolescent Psychopathology and the National Anxiety Foundation. Among her numerous honors, awards, and fellowships are the American Psychiatric Association Award for Research and the Presidential Maritorious Executive Rank Award. Dr. Rappapour's research has focused on diagnosis in child psychiatry, of attention deficit hyperactivity disorder, and obsessive compulsive disorder. During the past 10 years, her research group has been studying the clinical phenomenology, neurobiology, and treatment of childhood onset schizophrenia. Judith has authored or co-authored 300 scientific papers over that number and five books, the most well-known being The Boy Who Couldn't Stop Washing. Of this account of the experience and treatment of obsessive compulsive disorder, Oliver Sacks wrote, the dedication and care, the delicate and delicacy and sympathy with which she has entered the patient's lives, give her book an authority and a personal feeling which is deeply moving and impressive. And so today we welcome Dr. Judith Rappapour, who will speak to us about normal and abnormal brain development in childhood and adolescence. Welcome, Judith. Thank you very much, Judy Gardner. And I would like to thank President Johnson, Dr. Robinson, and this entire wonderful community for hosting me and my fellow speakers at what is, I think, really spectacular and unique conference. On a personal note, since Judy has already shared a lot of my autobiographical detail, I would like to say that the two years I had in training in Sweden and Uppsala were among the happiest and warmest memories that my husband and I have and that the sense of the community here and the caring bring back particularly fond memories of those days. I did indeed like it enough to have learned a fair amount of Swedish. Our oldest son is named Eric, spelt with a K. And he complains to this day that no one ever spells it right in this country. And I could give this talk in Swedish, but will not horrify my hosts by doing so. I also want to start my talk by saying that the work I'm going to talk about, which spans the last 12 years or so, is really equally shared by two colleagues, Javier Castellanos and Jay Geed, who have worked with me during all of this time. And what I want to present is really an odyssey, because as we talk about nature and nurture, increasingly we really talk as when we think about behavior as the brain as an organ. And much research is driven by new advances in technology. And I really want to share our adventure, as psychiatrists, the three of us, in looking at development in relation to the growth of the brain, particularly across the ages that are particularly important to all of us, from what most of us have been discussing, from toddlerhood, perhaps, till young adulthood, which had been very understudied. What I want to show you is that it's possible, if you are lucky enough, to be able to work in a research environment that will support very long-term studies, that you can get a unique glimpse at the growth and behavior of an organ that most people don't have the privilege to be able to sit and watch. I'm going to mostly be showing you information about a brain and about brains of children. And what I'm not going to have time to tell you about is that we know a lot about all of these children's families, their childhood, their psychological processes. We know their birthdays. We celebrate them with them. And this will sadly be omitted in the interest of time. From this presentation. But what we set out to do was to see, first of all, what's changing in the brain across these formative years. We wanted to look at developmental trajectories in relation to the measures that we're interested in, whether it's gender, cognitive ability, or psychiatric status. We have some ways of looking. You've heard a lot about TWIN method, and I'll mention that in some studies from Dr. Plowman. And what we realize is if we didn't know about the healthy brain development, we wouldn't be able to have a standard in order to understand the problems, possible problems in that of our patients. I might also add that if you're going to do long-term studies, we felt we were limited to just anatomic measures because it's far more problematic. It's really hard to decide what's the same task in a functional study for a four-year-old and an 18-year-old. And so really what I'm gonna be talking about are just straightforward scans of the brain. This is a picture of an MRI machine, and I'm sure many of you know it. I hope not too many firsthand, but certainly this and the kind of pictures that you can get from this machine will be nothing new to you. So I wanna start off first with saying just what we learned from a very simple and straightforward technique of assembling large numbers of children and adolescents and asking them to come and simply have MRIs at the NIH and in return for which we would give them a copy of a picture of their brain. They would present these at class, give lectures on it, get credit in science class for it and so on. Now this is a map of the time course of the events that determine what makes up a human brain. And a great deal goes on before after conception in the early weeks and months. And I wanna point out that everything we have to do in the NIH study is just this little period here so that much of the migration of the nerves, the growth of synapses, much of this has happened long before we start our study. But there are very important processes still happening in the time period we study, such as the overgrowth and elimination of synapses, continued myelination of the brain, formation of dendrites, these are connections between the neurons. And so as you can see our hopes were rewarded that we were able to make observations of development even though we were starting for an embryologist very late. This is just a picture to show how lucky we were that colleagues and research nowadays includes larger and larger teams of people with very diverse skills. But I don't wanna dwell on this but this picture is to remind me to say how much we owe a team of collaborating colleagues, mostly engineers at McGill University where they had a automated sequence that allowed us to get automated measures on about 60 or 80 different parts of the brain. And if you have, as we do by now, over 5,000 brain MRI scans, you badly need a fully automated process as you can imagine. And this is just a scheme of what our designs look like. This is age across the bottom here. And these are just individuals. And in fact by now we have many more. This is just to give you the idea that people start at different ages and they come back every two years. And so by now this is a much more crowded slide but therefore we can put these different parts together and study development over a long time course. All right, this is the first picture of data. And you'll see a lot of slides that generally look like this where we plot the volume, what the measure, how many cubic millimeters there are, as opposed to age across the bottom. Here males and females are presented separately. And the first thing you can see which really startled us is how different people's brain size is. This is just the total brain volume and this is what the raw data looks like. As you can see at the same age for the same gender, people differ by almost 40% of brain value. And this is quite remarkable, even people of the same height and weight. And because there's so much noise in that kind of data, you get enormous power by following groups longitudinally and that's why we connected the dots who are the same people who come back so that you can see that you get much less variance and so you can make much more sensitive measures with longitudinal information. And what you see here is here's the slide with the raw data, but what you can see is, and in these slides, red is females and blue is males, there's some difference between the genders. And if you look carefully, you can see that this is really something of a curve. That the brain reaches a peak size overall in the early teens and then slightly declines, but the curves are parallel for males and for females. And that the ventricles slightly increase, that's the middle compartments of the brain where there's just spinal fluid, that the white matter continues to increase. The point being, yes, you can see overall changes in this age range. And one of the first things that we learned that we were impressed by was how different regions of the brain mature at different times. So these arrows here refer to the peak volume, so the frontal lobe and the parietal lobe mature, at least get to their peak volume several years ahead of the temporal lobe. This heterocronicity came back to be important to us later as you'll see. And what we think this reflects, this overgrowth and then decline, actually has been reported before by a wonderful work of Dr. Peter Huttenlocker, who is a neurologist in Chicago, who studied these very rare and unfortunate cases where you could study young people who had died from accidents and look at different ages for synapses in the brain. And what he had shown was not just that, yes, there's an overproduction and then a pruning down in adolescence, but he showed that different regions have different peak maximum points. So this notion of heterocronicity or difference in timing for different regions had been known and we think that's what this is reflecting in our scans. So this is just a summary to say the first thing we learned is different. When you talk about brain maturation, different parts seem to be developing at different speed.  And I'll say more about that later.  And what you can learn now that it's 10 years later, we have a real perspective on the brain growth in children with different disorders, but just with the healthy children looking longitudinally, we see some interesting things. This is just a very short movie to show you the growth that you can see over these years of an important tract of the brain called the corpus callosum, which connects the left and right halves of the brain. Oops, I seem to have gone past it. Let me go, let me go back. Well, I seem to be missing out on this movie. Maybe I can get Pat to come back and help me with this. What the point of this movie is, is that in this case in a subgroup of children who are in a subgroup of children, who are screened, I think it's going now. Thank you so much. Is that it? Yes. What you can see, thank you. As you can see from this movie in a subgroup of children, this part of the brain, the corpus callosum, really changes very dramatically across age. And if you are willing to wait for years at a time, you can make the kind of movies of growth of the brain the way you can watch plants grow in infrared light. This is just showing the dynamic changes and the nose is over here. So unexpectedly, this is showing development in a front to back fashion. That's not true everywhere in the brain. And so this was a puzzle and a surprise to us. This is as it gets later, the changes are moving back there. I'm not gonna take time for the rest of the movie, it shows slight gender differences and so on. But it's to give you a sense of the potential of this wonderful non-invasive technique and what if you're patient, what you can learn with time. So what we've learned so far was that prospective studies are much more sensitive, that clearly developmental trajectories are going to differ for different brain regions and that we think these relate to overproduction and pruning of synapses in the cortex. And more about that later. Another thing that we learned because we were interested in using this wonderfully powerful twin technique to look at brain development and that some things were just startlingly genetic. We could tell who were the twins and who were fraternal twins as opposed to identical twins just by looking, for example, at the shape of the corpus callosum. There's an arrow here showing the MZ twins, whereas this white matter tract, the one we showed you the movie of developing, looks very different for dizygotic twins. That's not true of all brain parts. And in fact, if you compare volumes between the mono and dizygotic twins, to our surprise, that last developing piece of the brain, the cerebellum, appears to have the smallest amount of heritability, in the sense it has the least difference between the mono and the dizygotic twin for volume. These are plots of comparing one twin against the other and therefore you can see the correlation for monozygotic versus the correlation for dizygotic twins. So already we were very intrigued. It appears that there may be one part of the brain that is, quote, less heritable and develops later on in life. And that of course gets you thinking immediately about what are the kinds of later skills and input that one might need that this part of the brain may subsume. We're in the process of trying to pin this down further. There are many parts of the cerebellum as there are subparts to all of these areas that I'm naming so simply. So this is the beginning of work, not the end of it. Clearly though, in terms of just the raw structure, it looks as if at least in a gross sense that genetic factors are gonna be generally very strong, although there'll be exceptions, that there are these really big regional differences in terms of development and how heredity things are, and that we're very interested in the cerebellum as an input possibly to environmental influences. One of the questions we asked in terms of this curve, you know this overproduction of synapses and the pruning down is supposed to, in some general sense at least it was always my model and that of many cognitive neuroscientists, that this overproduction and pruning down that late adolescence somehow gives you a leaner, meaner thinking machine by the time you're finished at that point that perhaps is more appropriate for the tasks you're going to do at a certain age. In terms of brain volume, when we measure IQ versus total brain size or the size of any part of the brain, the back, the front, the white matter, the gray matter, we get a low correlation between, in this particular case, a correlation of 0.35, but highly significant between the brain volume and the size. But then we thought, well, what about this overproduction? If you're much more gifted, are you more likely to prune more synapses, grow more synapses? And the answer is nothing that we can find. These are these developmental curves for the, we just divided our large group in half and this holds up now with double the size of subjects. If you look at these curves for whether it's the highest IQ or the lowest, this isn't a wide range because these were all children in the healthy range, but there isn't any hint that there's a different shape, there's a different level, because I've told you you have slightly different brain, slightly, but significantly different brain volume, but in the sense of whatever this production is, we can't seem to relate it to some obvious and simplistic measures of function. Similarly, the frontal lobe which subserves many aspects of attention, I'm not gonna show you this, but whether you're very attentive or very inattentive, these curves look just the same. So there's a lot that seems like structurally given here. This is just showing the same thing with white matter, even cerebellum. Another thing that you can do with these is to see what's changing during this age range and I don't, you can take the white matter and each voxel, which are these little units that scans are made out of, you can correlate them with qualities of your subjects and what we notice was with age what seems to change the most during our child adolescent age range is a particular part of the white matter which Eric Candell, you're not quizzed on these talks, but if you remember Dr. Candell's talk, he did talk about a very important white matter track that connects Broca's area and Wernicke's area and that when severed can make people not connect and not have meaningful discourse and this seems to be developing across our age range very strongly because that's what changes the most with age. Now I throw this just to show you the power and the wealth of what this kind of approach can do. Well now that I've given you a background in normal brain development, let me talk a little bit about the clinical groups that we have in parallel been applying this to and what's been so wonderful has been the opportunity to have yoked groups, very much the way you would yoke, cattle and field. We have groups that were matched for age and sex that were scanned along the same time so that we could always compare their development over the last years. These projects all started in 1989 and are really reaching fruition about now and so I first wanna talk about studies with hyperactive children, attention deficit hyperactivity disorder as it is called. Most of you at least know the label, you define it in terms of the way the definition is currently operationalized by at least six types of evidence of inattention and or hyperactivity and fidgetyness that starts at least before age seven. You can only make this diagnosis in competent professional hands if there's really clinically significant impairment in several settings and usually the people that in as I say in conservative hands, it is still a fairly common disorder being anywhere from three to 5% depending on how the surveys are made. And one of the things we were asking just simply, this is a very controversial syndrome as many psychiatric syndromes are, there's no diagnostic tests you do for it. And we were wondering if you would see any brain abnormalities in this disorder and what the developmental trajectories are. And we wanted to know also if these had anything to do with clinical outcomes. Now based on years of observing hyperactive children and of seeing what sort of tasks they do well and they do badly and cognitive tests, there are various schemes for what the abnormality is. And the most popular schemes have been the relationship between the cortex and the basal ganglia, the quadate and putamen, they sort of literally lower nerve knots inside the brain. And these were areas that we were particularly interested in measuring. And what we found, and this is with 100 hyperactive children and 100 controls, more so, what we found is that both for males and for females, there's a slightly but significantly lower volume for the hyperactive children. And this is about the same degree from boys and for girls, although the male brain is larger and that's why these two are different from those two. And we also found some abnormality in the quadate volume, the part that was hypothesized, both for males and for females. The findings aren't absolutely identical, but they're more the same than that. And one part of the cerebellum, a cerebellar vermis we actually found was very significantly smaller, both for males and for females. We were particularly interested in that part because of our interest in regional heritability. So this is just summarizing what I've just told you. I wanna emphasize that none of these are strong enough findings to be diagnostically useful. So whatever takeaway message there is, I want you to see this as an area of interesting and I hope important research, but if nobody you know who has a hyperactive child with one very rare exception, which I'll talk about in a minute, should go and get an MRI scan, that's absolutely certain. In terms of this diagram, therefore we certainly would include parts of the cerebellum, but basically it supported the notion what we had all along. Now as I've made it clear, we're doing these long term studies and one of the most striking things about hyperactivity in children is that about 50% by the time they're aged 18 to 20 are do much better and about the other half keep on having continued problems. So we said well what's happening to these measures as they get older? And this really represents because of how noisy the raw data is, these are curves formed by almost 500 scans. And this is the curve for the healthy volunteers in yellow and the green is the curve for the ADHD. And statistically this doesn't change, it's what we call a fixed abnormality, it's non-progressive. And of course one of the question that everybody asks us is what about medication effects could this be because they're taking a drug?  And the curve is really the same, if anything. It looks perhaps worse in some years, but it's not really significantly different. So it's not a medication effect. And then of course you wanna know, well does either an abnormality at the beginning or the end have any prediction to how these children do? Because we followed all these children to find out, well are you in the half that got better or the half that got worse? And certainly these overall volumes don't seem predictive. So far they don't tell you that. But since we're still in the middle of these analyses, there's a hint that perhaps with respect to the basal ganglia, there may be some prediction for the girls. But basically no, this doesn't seem to do it. So in terms of what Dr. Maccabee was saying earlier, yes, this is one of the most convincing and by far the largest study that says yes, there's really a quotes subtle brain abnormality in hyperactive children. But on the other hand, it doesn't seem as if that's gonna have much to do with whether you're in the half that gets better or not. At least as we measure it now. Now one of the things that you've seen before in several people's presentation is that the twin measures give you an idea of how heritable a disorder is. And of all the child psychiatric disorders, maybe of all the disorders in psychiatry adults included, it looks like ADHD as we call hyperactivity these days is among the most heritable. And these are just various twin studies that make this point where the blue is monozygotic and the orange is dizygotic. The heritability looks like around 70% or higher. And we decided to try to look at environmental effects by searching, and this was one of the hardest searches we ever did for identical twins who were discordant for hyperactivity. That is where one twin was just fine and the other had ADHD. And as you can see from these statistics, this is incredibly hard to do. And what's more, it's probably, the heritability as we found out is probably even higher than this because some local twin studies try to send us discordant twins. But if you're doing very large twin studies, it's extremely hard to have clinical details on the non-hyperactive twins so-called. And we found that we got 100 referrals from people and from families of twins. We found out that by the time we boiled down this group, we had, and actually met them, it turned out that only about 15 pairs really met our definition of truly discordant where one had ADHD and the other didn't. Sometimes the so-called normal twin was really on a stimulant and the people who were sent us the twin study didn't know that. And other times they had a different disorder. And so we ended up doing what we thought was a very small study. But it was an important one because we're obliged to send all of our MRIs to a clinician. And so I can tell you that of the 400, just single-ten ADHD subjects that we had, 400 different MRI scans have been read as clinically normal. But when we started to do these discordant monopsychotic twins, we already had two just frank lesions in the affected twin. This is one where there probably is an old stroke that children can have very minor strokes even before they're born or around the time of birth. This is not common, but one of these was in this group of this very rare pair of 15-year-old twins, discordant for ADHD. So in other words, there was some abnormality and something special. If you have identical twins, you should get an MRI if one has ADHD and the other doesn't. A second known abnormality had a very big area here called caven septum polysidum, which is very unusually large, and when it's that large, does go with various behavioral abnormalities. So we found this, but even in the others for which there wasn't any lesion, these two, the affected twin, had a smaller frontal lobe, smaller caudate volume. Interestingly, they didn't differ in the cerebellum, which may be the quote's less genetic part of this disorder from our formulation. At any rate, so we do think phenocopies do occur, even though there's a very strong heritability, and they're however probably pretty rare in ordinary environments, and probably some aspect of this circuit of the basal ganglia seems to be particularly vulnerable to damage. Again, this like all of our other studies is pretty much still ongoing, and we are in the process of looking at the white matter tracks for this discordant pair sample to see where the wiring is wrong for the others for whom we don't have frank lesions. This is, as I say, just the beginning in a way because functional studies of selected groups I think will be particularly important. So this is the fact that we were interested in huge numbers in longitudinal studies that made us choose anatomy, but I think they'll be very interesting functional studies to localize which parts of the brain are really working in the most deviant way, and I think more functional correlates will be important for the future. In the last third of this talk, what I would like to do is talk about another group that has been particularly perplexing to us, and that is cases that shouldn't happen, which is like many psychiatric diseases, childhood schizophrenia really starts in typically late adolescence, early adulthood, and we had collected a sample and been assembling a sample over many years of children who have a disease that, quote, shouldn't happen because they became schizophrenic with an onset before their 13th birthday. We had a number of research and clinical reasons for wanting to look at this very ill group, but one of the advantages of studying a group in adolescence is you can look at the brain development in a group at that age. This is just epidemiologic data that happens to be from the UK but could have been from any of several other countries of the rates of admission with a diagnosis of schizophrenia. And as you can see, when you get down below the age of 14, and this is age at admission as opposed to rate, and once you get down below the age of 14, it becomes extremely rare. And even we, in studying this, and by now we have closer to 1500 referrals and have screened many children, and actually just a little bit over 70 children have participated in our very complex study to date. And I'm not gonna, of course, begin to tell you about the many other aspects of the study and the families and the relatives of these children. But what I can say is that in schizophrenia in general, what people see is that you have a smaller brain volume, larger ventricles, some medial temporal lobe structures, particularly the hippocampus may be smaller, and that in adult years, this isn't seen as progressive. When we looked at the childhood data, this was a striking that they have a smaller brain volume, even more so, and increased lateral ventricles, and it seems as if this seems somewhat more dramatic. Now, in terms of what forms schizophrenia or any disease, as you know, it's going to be a combination of certainly genes. There's evidence that pre- or pre-natal complications are important, and there's an important theory that synaptic pruning may have something to do with this. It's a selective decrease in the gray matter volume, what you see in schizophrenia, and this has been a hypothesized in adults as being a very important process. So we set about seeing what's happening during adolescence now that we know so much about the normal development and we know about the fixed lesion in the hyperactive children, and we set out to compare the schizophrenic children. And what you see here, the first thing we noticed was and the red are connected dots for schizophrenic children in some of our early studies, and the yellow are normal controls. Again, the dots connected because these are children who returned every two years, and the blue are children who were sent to us by clinicians and families who thought they were schizophrenic, but turned out to have another kind of chronic disorder which was a very severe kind of chronic depression, some becoming bipolar, but none had the very severe disorder of schizophrenia. And what we found is unlike what's seen in adults was a clear increase during these years. This is a plot of the volume of the brain ventricles, and this is baseline and onto-year re-scan. And then we realized that this is really major and this is not the usual plot, this is just the percent change between the ages of about 13 and 18. And we see unlike the ADHD and unlike certainly the healthy children which are in yellow, what we have here is a very impressive loss of tissue in the gray matter compared to the controls.  And this is much more striking in adolescence than it is in adulthood. This is a slide of an effect size which is a statistical term to say how big an effect is the difference in a study. In our case, the difference in change between the healthy controls and the schizophrenics. And that's our study up here, the effect size, whereas a few other adult studies had shown a little bit of an effect but really not very much, whether it's for cortical gray loss or ventricular size in changing. During these adolescence, these children are not developing normally their neurologic exam, which improves with age for healthy children, as shown by the yellow dots. You may have fewer neurologic signs as you complete adolescence, but our patients, they don't change across this age range. They're learning less in school, understandably, because of their illness. And what you see, this is now the more familiar way of just volume plotted against age. You see this progressive loss, particularly in the frontal and temporal lobes. So this is a kind of summary of where we are now that we're finding that the longitudinal study is very important. We've talked about the strong genetic input in ADHD, but which appears to be a fixed early lesion that doesn't change. And now we see the schizophrenic children where particularly for loss of gray matter are very much changing across this age. One other technique of how we look at this has been very important to us, and that's been this another group at UCLA that has another way of showing the cortical change much more graphically in pictures that you recognize as actually what brains look like. And if you can subtract, because I told you that the controls come back every two years also, so we can subtract patients from their yoke controls at age 12, 14, 16, 18, and so on. And what's clear is that the schizophrenics are losing matter over time, a great deal more than are the healthy controls. But what was striking to us was that even where they were losing this, there was a real wave of change. When you take the young patients and subtract them from their controls, the difference is much more in the back of the brain. Five years later, it's all over. And so across adolescents, oh, and I should say that this is not happening with this contrast group either. So across adolescents, this is happening also on the medial side of the brain, you're seeing this progressive loss. And let's see if I get this right this time. This should be showing our movie. You can make a movie of this if you're willing to wait 12 years to do it. And this is the movie of the progressive change of what's happening in adolescence between our patient group, which is very different from what would happen with hyperactivity between the ages of about 13 and 18. But this is a time limited window in adolescence during which in normals, you're getting this overproduction of synapses and loss. What you're getting in the schizophrenics appears to be mostly just a decline. An interesting point here, and I hope I don't lose you on this, is that at least in studies in adults whereby comparing mono and dizygotic twins, they can see which parts of the brain disorder are more heritable. Remember, I've told you that our patients go from back to front. The most genetically determined aspects seem to be the certain parts of the frontal and the temporal lobe. Whereas what our patients do is start from a totally different part of the brain. We have a wild speculation that perhaps it was an environmental trigger elsewhere in the brain that sets it off. And yet, you end up with particular deficits in a region that appear to be most heritable. One question we're always asked is, well, do your children end up with dementia and neurologic disease because that's not characteristic of schizophrenia. And the answer seemed to us when we began, this rate of loss couldn't possibly continue. And we do indeed find out, this is statistically significant, though it may not look so, that this rate of loss as they get past age 20 does decline. And as our cases get older, we look like the adult cases. So it looks as if adolescence is a time limited window in which these very dramatic changes are occurring. And just to make things more complicated and to leave you, because I'm about getting toward the end of the enormous amount of data that I think I've perhaps been overwhelming you with, I want to leave you with a puzzle about this information because on the one hand, we have our more severe patients within our group of quite ill children have more loss. But on the other hand, when we look at our children who in our hands with the adjustment of medication and advice to the family and protracted hospitalization at the NIH, our group also improve over the years. We find that the ones with the more loss also are showing, I'm sure you wouldn't have voted this way if I asked you to raise your hands but are finding more clinical improvement. So what does this mean? Is it possible? Certainly we have evidence that genes are important in this. Synaptic pruning may be excessive in adolescence, but one question is what does any of this mean? It's clear that we can say that schizophrenia is a disease of abnormal brain development. And the late changes that we're showing here in adolescence, they can be a reflection of late maturation due to an early lesion, as some would suppose. I think that it's probably a later action of genes or some trigger that act later in development, even though there were clearly earlier impairments. And a third possibility, and these are not mutually exclusive at all, is that it may be a reaction to if you have an illness and your synapses aren't working right, perhaps this is a case where it is a plastic response to an illness, and it's trying to in fact get rid of the bad parts to help you improve better. I think all of these are possible. And so I leave you more with questions than with answers. It's clear there are strong genetic effects. It's clear there are many avenues for which you're going to have environmental effects, which may be our most important and most positive avenues for treatment, that you can see so-called fixed lesions, such as ADHD, or progressive lesions, such as with schizophrenia, that I don't think we can blame drugs for this, even though that's a big complication in psychiatric research, because the stimulant drugs didn't matter with the ADHD children's developmental abnormality. And for the schizophrenics, we had this contrast group of children who have chronic and very severe mood disorders, and they're not showing this at all, and many of them are on all of the same drugs as our patients. And I think that these are really just going to begin to let us know something about the candidate genes that give us clues for looking at in terms of what underlies these abnormalities. I just want to close by mentioning that in addition to Javier Castellanos and Jay Geed, who are really co-workers on all of these, that the Montreal Group and UCLA and geneticist colleagues are very important in these studies. Thank you very much. Like to invite our panel, reassemble here. We'll take questions from the audience again, of course. The nice thing about the NIA is you can work on a study for 12 years, and it takes that long to get it straight, and even then we mostly don't get it straight. I've been asked to announce that those of you who will be in search of coffee should look in the forum. That's the building to our left here. Since it's raining outside, coffee will be available inside. It will be in the forum, be up the stairs and into the next building. Oh, one other thing, too, this evening, we have our banquet starting at 6.30 and our talk is scheduled for eight o'clock. If you have a ticket for the banquet, you're welcome to come to the banquet hall in the marketplace. If you do not have a banquet ticket, you can still hear the talk at an overflow seating in Alumni Hall, which is in our Student Union building upstairs, and there'll be signs pointing you to that way. Okay, do any of the panelists have any questions or observations? Dr. Kagan. That was really lovely, and those are the kinds of data that we need that will build us toward understanding. I just have one question. If you remember the slide you presented of IQ against volume, and you presented the scatter plot, it's always been my experience that when you take abstract concepts like that, that if you get a correlation of 0.3, it's because 10% are showing it, and in that scatter plot, it's just those nine kids in the lower left. If you took out those nine, you wouldn't have much of a relationship. It's the ones with the very small volume. There have been about, no, I certainly agree with your observation of our very scattered data, but I can say that there have been over a dozen studies with very large numbers of adults, and they all get, ours correlation was 0.35, they all get between about 0.35 and about 0.40, and so there have been dozens of studies that look all exactly the same between volume and IQ. That's right, but suppose if we had all those studies, it was, they're always due to that 10% down at the low end. In other words, let's assume that that's honest, that is the correlation in nature, 0.3 to 0.4, but let's take all these studies and look at all the scatter plots. It could be that it's those 10% way down here, if you got rid of them, then there'd be no correlation. Is that a linear relation, in other words? Well, I think that's the nature of correlations in general. Of course we eliminate what are considered outliers, but from a statistical point of view, we wouldn't have any way of deciding that we should throw out one particular group than the other, because it's a fairly, it looked like the distribution in our group was rather normal, and so it would be hard to rationalize throwing out one piece rather than the other, and I think the distributions in the adult studies that I've read looked about the same. Do we have any other observations? I have a question, I mean, just why is the cerebellum take so long to develop? We don't know, in the twins, we started to look at certain obvious questions and were wrong on everything, the cerebellum's known for motor control, and so we gave exercise questionnaires to all the twins, and we thought maybe we'd have differences between ones who were couch potatoes as opposed to ones that were jocks, and we had a surprising number of monozygotic twins for whom that was the same, and the answer was not a hint, and we also looked to see if some were more rhythmic, rhythmic, you know, were some tapped dancers and others had two left feet, and the answer was forget about it, so we don't have a clue. I have a question here. How many different types of brain lesions are found in children with ADHD? I wanna stress that this was an extraordinarily rare event that we had to comb the United States, first of all, for identical twins who were discordant. As far as just the typical hyperactive child, we didn't find any in hundreds and hundreds of scans. We also found no chromosomal abnormalities. We did this as comparison for other groups, but there's no medical tests that we would recommend worth doing. We haven't found any in our ordinary hyperactive children. So questions that could you elaborate on what role prefrontal lobe dysfunction plays in ADHD, or is research focusing more on the basal ganglia? Right. Well, that's a very good question because it reminds me to stress more than maybe the circuit I showed did stress that people think in terms of circuitry and that the frontal lobe basal ganglia loops seem important in the few functional studies that have been done, the connectivity between them. And I don't think that any of the studies I know would particularly point to one or the other so far that they've even been enough to address that. I understand the corpus callosum is smaller in the male. What is its significance in male-female differences? I would have to pass on that. I don't know the answer. Anybody else wanna take a guess at that one? Eleanor's heard it too. I have a question here that this is slightly different. All I'm waiting for some more questions come here. So would everyone on the panel please share with us if they are parents themselves and if their children ever influenced by their research or if their children ever influenced their research or area of interest? Yes, I'm a parent. I have two boys and it's kind of an interesting question because one thing I've noticed about people's study attachment is they often don't have children. Disproportionately. Have you noticed that? So yes, I do have two children and one is adopted. I inherited him from a wife who died who had been by a former marriage. So you do experience the differences between genetically related children and those who aren't. So I guess they did influence me. I influenced my, one of my sons, who I really wanted to go into psychology by trying to get him to go into psychology and as a result, he's a journalist. My children were control subjects for some of our studies but they said that my husband and I worked too hard and they wanted to do something else. I have one daughter and I was too much of a psychologist. When she was two years old, we had returned from the Cincinnati Zoo and in those days, the gear shift was on the wheel and I put it in gear and the car was in the dry. She wanted to stay in the car so we went, my wife and I went in the house and two minutes later we heard an enormous noise. And as she obviously had released it and fell many, many feet, fortunately she was unhurt. So then I made an error. I was gonna be a good child psychologist. Should we talk about it or not? And I made the mistake of deciding, no, we'll not talk about it. She was unhurt and we didn't, nothing was mentioned for 25 years. And then one summer afternoon, I wasn't thinking of it and I said to her, we're having ice cream. I said, what's your earliest memory? And she shocked me by saying, daddy, you should have, we should have talked about it because I often thought about it and I never knew whether it was fantasy or reality. So, and now I'm gonna give you the insight about anybody who knows children understand this. I said, why did you release the break? I remember, she's two years old. She said, because you always took the car to the end of the blacktop of the driveway and this time you didn't. And I was trying, in other words, the child too is so sensitive to rules that she was trying to move the car to the edge of the blacktop. I have three adopted children. The eldest was adopted when she was 10 and the two littlest one, when they were each seven months old, they're very different from each other as I think one's natural children would be as well. But the issue of adoption came up. Your story is so interesting to me, Jerry, because my little daughter, when she was four, was walking along with me and one of her little friends and she said to her friend, do you know why I wear glasses? And her friend said, no. She said, well, it's because I can't see out of my near side. And then she said, and that's why you adopted me, isn't it, mommy? I thought, what? And I couldn't. Then I remembered that when she was two, I had taken her to the eye doctor and said, I've noticed that my little girl, when she looks at a picture book, his eyes right down on the book. And he said, oh, she's extremely near sight and he looked at me and at that time I wasn't wearing glasses. He said, I see this doesn't come from you. Is your husband very near-sighted? I said, well, she's adopted, so that's not relevant. Something was going around in her mind for two years until she was four. Oh, great. I'm childless. That's wrong. So you said, that's relationships. Oh, thank you all. Well, here's, we'll allow you to speculate a little bit here. Are the decreases in neuronal activity in the temporal lobe responsible for hallucinatory characteristics seen in schizophrenia? There have been some correlations that do relate specific symptoms in schizophrenia to changes and some have done for a particular part of a particular gyrus in the temporal lobe, particularly. There have been several studies that did that. In our particular study, we didn't find such a correlation, but they have been reported. Another one said, do premature babies make up the brain growth out of the uterus at the same rate they would have grown in utero? That's getting to be a big area. I know that in our hyperactive, in our healthy children, we didn't have children who were premature, but in the ADHD sample we did, and those with the smaller brain size were overrepresented with children who had been premature in that sample. I believe there are studies that suggests that within non-hyperactive children that there's a slight difference that stays long term, suggesting that in the very last weeks of gestation, there may be some extra growth factors that are important. Question, are there any studies on brain volume or brain matter in criminals? Not that I'm aware of using these newer techniques. Well, here's one. Do you believe that ADHD is being overdiagnosed and overtreated? If so, what might be the consequences and how could the diagnosis be made more specifically? I think that's a very important question, and there's different information that goes both ways. I know of certainly many stories where people feel that stimulants are being used in children who are relatively mild. When you look at some population studies, some epidemiologic studies, they tend to suggest that many hyperactive children, if not most, in fact, aren't being treated at all. So it's hard to know what's growing recognition and treatment as opposed to really overdiagnosis. I do think, though, that it's worrisome that today the HMOs will only pay physicians to prescribe medication and not to do other things like counseling. And so there may well be pressure on young doctors working for HMOs to feel like they should do something more. But I really wanna stress that the epidemiologic studies, I now do not suggest that there's a lot of other children that are very significant getting treated that shouldn't be. Well, here's a question again on ADHD. Why is it that stimulants are successful in reducing symptoms in ADHD? Stimulants are fascinating and really complex drugs because what they do is they focus on task behavior and they do it for everybody in general, whether they're hyperactive or not. They were used in the war for pilots and people who had long-term, tedious tasks. And hyperactive children, when they need to do reading or math, move less on stimulants. But if they're in gym class, like football or basketball, they move more. So it's more to do with focusing attention to the task and it's a very complex thing. As far as the biochemistry goes, dopamine is thought to be very important, but that's not set specifically pinned down. This question here, would you please discuss the heritability of obsessive-compulsive disorder? There've been very few twin studies and it appears to have some heritability. What's always fascinating to me about obsessive-compulsive disorder is the way, even when two identical twins have the disorder, the way the symptoms can be totally different. And I don't think anyone really understands symptom choice. I'll tell one anecdote, since I've given so much formal data, which is that we had identical twins in a study from a family that was not neat and not religious. And one of the twins washed all day and the other prayed all day. And each one thought the other was very peculiar. That's wonderful. That's wonderful. That's wonderful. Do you think childhood onset schizophrenia is related to viral infections, or here we have another one, allergies, nutrition? As far as the viral theories in adult schizophrenia, there are some very convincing studies that viral infection at a particular time of pregnancies, these done with very large numbers at a time of a flu epidemic. That may slightly increase the risk for schizophrenia in women pregnant at those times. In our very small sample, we don't think that's a risk factor by the crude measure of all their birth records because we looked at the birth records for all of our very early onset patients and they don't differ from that of their well-symptom siblings or of population norms. So for our cohort, I think there's some other mysterious and hopefully very interesting and to be discovered reason why they got sick so young. But for adults, I think most people think that that's been shown. Here's our follow-up question on this. Could you briefly review the literature on treating early psychotic symptoms in children with anti-psychotic medications with the idea of preventing the full-blown disorder? What do you think of such a treatment program? That's an area of very active research as to whether it's worthwhile taking very low doses and treating it. The very low doses of some of these anti-psychotics do appear safe and they appear quite effective. And so I don't know if you'd know what the rate are. Because schizophrenia isn't that common, you'd have to have very, very large numbers to be able to get a group that is not schizophrenic that you're sure are gonna become schizophrenic. Most of the people who would be in such an early study probably have mood disorders and the low dose of drugs would certainly work for them. So I think it's technically, in theory, it's an idea worth doing. But technically, I think it's very hard because you need such huge numbers of people, most of whom who will have something else. And whether that many people should take a drug for so long, I have something of a bias against it but the jury's not in. Any other questions from the panel here? In that case, speaking of stimulants, it's probably time for coffee at this point and so we'll adjourn until three o'clock.


But I wanted to ask you to begin, since you were here last year, you were at IFRI's World Policy Conference last year, take us through the past year in terms of cooperation and competition in the space area by the international community, in which direction are we moving? And can you also then go back a decade and tell us what have been the major changes in space? In fact, since last year, we had a number of changes because of what is made in the US. Because in space, you have six large space powers, the US, China, Europe, Japan, Russia and India. But the US are definitely the biggest space power. And last year, a new administrator has been appointed at NASA, Jim Ronenstein. And the Trump administration tried to change a number of points in the US space policy. And I would like to insist on two points, which are, in my opinion, quite important. The first one, a new interest to go to the moon. But to go to the moon, not to come back to the moon, because you probably saw the many movies existing on the moon with the moon landing 50 years ago. The last one is The First Man. It's a very good movie. But the idea is to come back to the moon, but with private initiative. And this is why NASA is now contemplating what is so-called deep space gateway with private companies, which could be interested in coming back to the moon. So this is the first point, moon. And the second point, you know that in the US today, there are six forces in the army, which are the US Air Force, the US Navy, US Army, the Coast Guards and the Marines, and five today. And so President Trump wants to add a sixth one. It's a view because, in fact, the US are very active in the field of defense systems, which are developed for space. We have a budget for NASA, which is $20 million, a budget for the DOD, which is roughly the same, $20 million. But there is obviously a political will of President Trump to create a sixth force. And we will see if he does it. And these are these two very, let us say, important factors which are today shaping the new landscape of space policy worldwide. And do they affect the ability to cooperate by the international community? For the moon, it is clear that we will have probably the follow-up of the International Space Station. But on the International Space Station today, we have the US, Russia, Europe, Japan and Canada. And two space wars are not in the station, India and China. And the big question mark is, are we going to see China and India being a part of the back to the moon? It's an open question. There are pros, there are cons. It is clear that it's a project which will be very, very expensive. China this year will be probably the space power with the biggest number of launches, more than 30 this year. And so there is a question mark, but in the same time, you know, better than me, the relationship between the US and China, which is not so easy. But this is an open question for international operation. And it is clear that if we have now a six-force for a defense, it will open also a number of new issues. And probably it will reinforce the will of other space powers to have also a military space program. Tell us a little bit about Russia's space program these days. How important is it? Russian space program is quite important. They have fantastic heritage. But as a matter of fact, they are suffering technical difficulties. You probably saw what happened two weeks ago when Russian cosmonaut and US astronaut tried to go to the space station. And after 90 seconds in the flight, they were obliged to eject, to jettison the Soyuz capsule and to come back with a parachute because there was a malfunction in the Soyuz launch vehicle. And there are a number of quality issues in Russia. Could you talk now a little bit about this incredible amount of data that is assembled by the space satellite system? Who owns this data? What happens to it? And how important is it to the world economy today? In fact, the question of data is absolutely crucial because we have more and more satellites sending more and more data. And so they transmit data for telecommunications, but this point is not really an issue. What is an issue is what to do with the data related to Earth observation and in particular data related to observing climate change. And there are two options which are on the table. There are some countries which say that this data must be proprietary and stay in the country which owns the satellite and some other countries, and this is the case of France and Europe, which have an open data policy. And I think, personally, I think that it is the right option because with all these satellites, we have today two points which are at stake. The first one to have a kind of standardization of data because when you observe the Earth, if you don't observe exactly the same data, you will have a dispute between China and the U.S. when the U.S. will say to China, you pollute a lot, we have a lot of greenhouse effect disease and China will not accept it. And so we need to standardize the data and this is what we are doing now. And after this, this data must be in open policy and in my opinion it's quite important because it has a very strong political effect and it creates also a number of startups which will use this data which will develop new models and I am sure that the future of space is probably relying on open data policy. And when you say that we're moving to standardized data right now, explain to us what that means, what is standardizing? For instance, if you observe the concentrations in the atmosphere of carbon dioxide, there are many possibilities to observe these concentrations from space. You could measure the age of a kind of virtual colon with carbon dioxide. You can describe the clouds and so on, but if you don't observe exactly the same data, you will have a lot of debates between scientists. And this is why we are now preparing and I hope we will be able to sign this chart during the next one-planet summit organized by President Macron. The first one happened in December 2017 in Paris. The second one last September in New York City and the next one is planned for an Nairobi next March and I hope that Nairobi will be able to sign a charter defining exactly which data should be observed in order to have this open data policy. And can you explain a little bit more about this forum where this will be discussed? Is it, does it have any private sector companies that are members or have a way to put input into? Yes, of course we have a system with satellites which are owned by the government. But after that the use of data is made by private companies. And these private companies use this data which are free and with this data they will create value because in fact we have to consider this data as a kind of infrastructure which is provided by the government. Since we are sitting here on the shoulder of Africa, tell us a little bit about Africa's role in space. Africa now is opening the space chapter because until ten years ago there was a very small number of space powers for a simple reason. Owning a satellite was immediately several hundred million of dollars. And now because of the digitalization, because of the miniaturization, the cost of the satellites is decreasing very, very strongly and you have more and more countries which have a space program. Ten years ago we had six big space agencies, today we have 60, ten times more. And so in Africa, Africa was out of space until a few years ago and now you have a space program in Algeria, in Kenya, in Egypt and probably the most important, this is here in Morocco because Morocco decided to buy two very smart Earth observation satellites to help to manage the development of Morocco. We launched the first one last year from French Vienna and the first one is so-called the Mohammed 6A and the next one, the Mohammed 6B, will be launched on 20th November from French Vienna as well. But there are very, very smart satellites which are manufactured in France and this is what we used to call the African chapter because now Africa is using more and more data for its development. The United States in announcing the space command emphasized Vice President Pence certainly emphasized his desire to maintain the superiority and military, the military realm in space that the United States has today, he says, on Earth. Is that a realistic objective? Is it an objective that we should wish happens? I think that it is a realistic objective. I am not sure that it will be at the end what is described today but we had this situation 30 years ago when President Grigan decided to develop a Star Wars and there were a number of projects which finally didn't exist but the consequence has been that the federal budget injected a lot of money in the U.S. space industry and strengthened considerably the U.S. space industry and I think that nobody knows what will be at the end of the day the consequence of the decision of President Trump but everybody knows that it will reinforce considerably the U.S. space industry. For my last question before I throw you to the audience and appeal to their mercy, talk a little bit about commercial travel in space, how Elon Musk is doing, how Jeff Bezos is doing, what are the patterns developing in commercial space travel? To be very honest, I have a lot of doubts for the next 10 or 20 years about space travel because we cannot be all of us here, we cannot be astronauts. When you go into space after eight minutes of very strong gravity, you are in zero gravity and most of people are immediately sick and it's very, very difficult and there are some projects for instance from Elon Musk with the big Falcon rocket when they say that they could go from Paris to New York in 30 minutes. Okay, it can be done but it will not be at all as in the jetliner because it will be 30 minutes in zero gravity so it means that after a few minutes most of the people will be sick and so I think that it will not happen in the coming years. After that, perhaps after 20 or 30 years we will find the specific devices to create artificial gravity or something like that but in a nutshell in my opinion it is not for tomorrow. And Europe should, Europe aspire to a role in commercial travel in space? We have a number of projects in Europe but frankly speaking there are a lot of projects in the US, in other countries but today these are only futuristic projects and I do not see space travel for the next 10 or 20 years. And what about travel on earth that we talked about last year or some in our panel on the interconnected nature of the internet and there was discussion of the ability of people in Sao Paulo to telephone for a not necessarily a spacecraft but a high altitude vehicle. How is that developing? In fact, we have also a number of projects which exist but during the last year we had the kind of strengthening of some projects. We spoke last year about Galileo. Galileo last year had 50 million users now we are at more than 500 million and for a very simple reason is that the ships which are on the smartphone are now equipped with Galileo worldwide and so it means that every time someone buys a smartphone is a new user of Galileo because Galileo is 10 times more accurate than the GPS and your smartphone choose by itself the best accuracy and so one or two years ago everyone was connected to the GPS and in three years from now everyone will be connected to Galileo and it will be the reality of what I said last year because when we started to speak about Galileo a lot of people told me that Galileo is the European GPS and I answered that in three years we will say that GPS is the US Galileo and I am sure that it will be the case. Very good.


Welcome back. In the previous lecture, we defined the Lebesgue measure on 0 1, the uniform probability measure on 0 1, which is an uncountable sample space. We also defined on the real line the Lebesgue measure, which formalizes the notion of length. So, these two measures are, so the Lebesgue measure on 0 1 is a probability measure and the Lebesgue measure on R is not a probability measure. It is just it is an infinite measure and both these are defined on the corresponding Borel sigma algebras on 0 1 or the real line, which are generated by open intervals. Today, we will consider another uncountable sample space. This model is called the infinite coin toss model. In this case, the sample space is the uncountable set 0 1 power infinity. So, each elementary outcome corresponds to an infinite coin toss. So, each little omega, so if you take a little omega in omega, it will be of the form omega 1 omega 2. So, these are bits. So, each elementary outcome is a infinite binary string and we know that by Cantor's argument, we know that this is a uncountable sample space. So, essentially what I am doing is calling head is 0 and tail is 1. So, this is an uncountable sample space and we want to do, we want to assign probability measure on this uncountable sample space. And you know that, because the sample space is uncountable. If you consider all possible subsets of this omega 2 power omega is 2 large sigma algebra to assign meaningful probability measures on. So, we have to again settle for some smaller sigma algebra, only consisting of those subsets of omega, which are in some sense interest of interest to us. And then, we will try and then what we will do is, once we define an appropriate sigma algebra on omega, we will assign a probability measure, what is what we like to be a uniform probability measure on this omega. Ideally, what we want is that all no particular string being preferred over any other particular string. That is the kind of we want intuitively, we want an uniform measure on this space. So, that is what we are building towards. So, this is also a very canonical probability uncountable probability space. And in some sense, you can prove that, what I am going to say is, has very close correspondence to the Borel measure on Borel sigma algebra and Lebesgue measure on 0 1. If you write it as binary strings. So, it is fairly close to what we have done, but because it is in the language of coin tosses, the flavor is a little different. So, far you have each outcome is a infinite binary string. So, in this, now the question arises, we have to put a sigma algebra on this. And as I said, if you put 2 power omega, it is too large, it is too complicated. So, what I want to do is, first start off with some collection of subsets, which allows me to describe the outcome of, let us say the first n tosses. Start with the finite set of tosses. So, let me say that, F n. So, this is going to be a collection of subsets of omega, whose occurrence can be decided by looking at the first n tosses. So, I have not really called it an event. Note, I only called it a subset of omega. I have not yet built my sigma algebra on this. So, I have deliberately avoided calling it the collection of events, because by event, I mean something very precise. I mean F measurable sets. So, this F n consists of, so F n consists of collections of subsets of omega. Omega itself is all these binary strings, infinite binary strings. And all possible, you take a certain collection of subsets of omega, whose occurrence or non occurrence can be decided based only on the first n first n coin tosses of any outcome. So, by this I mean, so if I want to ask, let us say an example, let me see. So, I want, let us say I am interested in whether or not the, so for example, I am going to look at at least 2 heads in the first n tosses. This is something I am interested in, let us say. I want to know, if there are at least 2 heads in the first, so I have an elementary outcome, which has an infinite bit string. I am looking at the first 10 bits and asking if there are at least 2 heads in it. So, this is a, so if you call this event some E or something, then E is an element of F 10, because I can decide whether E occurs or not by looking at the first 10 tosses. So, this is what I am looking, this is what F n contains. It contains all those subsets of omega, whose occurrence or non occurrence can be decided for certain by looking at only the first n tosses.  So, one thing that is immediately clear is that, something that can be decided in 10 tosses can also be decided in 11 tosses. So, if some E is an element of F n, it is necessary in an element of F n plus 1, F n plus 2 and so on. So, if you can call, whether an event occurred or not in 10 tosses, you can do so in 20 tosses, no big deal. So, these are all nested. So, I will write that down. So, this is easy to show claim, F n is contained in F m for all n less than or equal to m, this is very easy. So, this is, so I have defined F n in a certain colloquial kind of a way. So, the correct way to define F n mathematically is to say that an E a subset, let us say E belongs to F n. If the first n bits follow a certain conditions, let us say in this case the condition was 2 heads, at least 2 heads out of 10 tosses. So, I am essentially looking at the first n bits and I am mandating that to be a certain particular subset of the 2 power n possibilities in the first n tosses. So, more formally, I think you will understand what I am going to say now. So, if you want to write this more formally, we will say that A belongs to F n. If there exists some A, I will write A superscript n that is a subset of 0 1 power n such that A equals the set of all omega for which omega 1 omega 2 dot dot omega n. If you look at the first n bits here, this is in this A n. So, is this clear? So, I am say this A index by I am superscripting by n. So, this is a subset of 0 1 power n. So, 0 n power n gives you all possibilities for the first n bits, but I am mandating that the first n bits of my set of interest should be a fixed subset of 0 1 power n. So, it should have a certain property. For example, in this particular example, the first the A n consists of those n bit patterns in which the at least there are 2 heads in the first n. So, you should look at 10 n equal to 10 and say that you look at in A superscript n will include all those patterns in which there are at least 2 0's in the first n. So, essentially this captures the property of the first n bits that I want to decide whether it occurred or not. Actually this is all this is very simple step I am I am coaching it in certain notation to be formal this I suppose this is clear. So, A I say. So, this is the definition of. So, I am saying that A belongs to f n if there exists some the first n bits have a certain property. You can look at this A n as a subset of 0 1 power n that satisfies the property I want for the first n bits. So, remember this A is an element of omega. See A is not an element of omega A is a subset of omega for which the coin tosses satisfy the certain property for the first n bits. So, for example, so if let me take another example.   So, we say that f 3 so it is an element of f 3. So, we will say A 3 will consist of the first 3 bits in which the third bit alone is a head the other 2 can be anything there will be. So, how many possibilities 4 possibilities the third bit is fixed as head the first 2 can be anything. So, this A superscript 3 will consist of those 4 strings of triple bit 3 bits. So, is this clear. So, it is very simple stuff I actually couched it in a certain notation, but I hope this will be clear. So, what we really want so I want to eventually say I want to eventually assign some uniform probability measure. So, ideally I would like to say that as a particular n bit pattern should have a probability 1 by 2 power n that is what I want to say. So, I want to say that each bit being 0 or 1 should be probability half. So, many string of a particular string of n bit should have probability 1 by 2 power n that is what I want to say, but on the other hand I have to put a proper sigma algebra on it and do it formally that is what we are building towards. Now, what you can show another claim f n is a sigma algebra you can show this you try this as a home work. So, f n the set of all events whose occurrence or non occurrence can be decided in at most n tosses is a sigma algebra you can prove it try this as a home work. Now, given that f n is already a sigma algebra one might be tempted to say that my measurable space should be omega comma f n. So, if we take a big n let us say I take n equal to some million. So, I take some very big n and I say omega comma f n is going to be my sigma algebra it is a valid measurable space. So, I can put some probability measure on it to say that any n bit pattern has probability 1 by 2 power n the problem with doing that. So, if you take. So, if we take let us say omega comma f n as a measurable space. So, elements or sorry subsets elements of f m for m greater than or equal to n cannot be assigned probability measures. So, what happens? So, even if you take n equal to million or if I want to answer the question what is whether my million plus 1th toss is a head or not I will immediately cannot answer it. So, no matter what n you take if you take f n as your sigma algebra I will immediately ask you question about how about my n plus 1th bit or is my n plus 1th bit head or you know some question about something beyond n. So, then you will not be able to answer it because I am only taking events in elements of f n as my measurable sets. So, this is a little bit of a problem this is a sigma algebra there is no problem, but it is not a nice enough sigma algebra it is not a rich enough sigma algebra to help us characterize even beyond n nth coin toss occurrences beyond nth coin toss. So, is this clear? So, we have to do something else. So, we have to look beyond this finite horizons. So, we do the following we define. So, let us define f 0 equal to union i equals 1 through infinity f i you know I mean maybe I should actually write as I keep saying no maybe I should just write that is better notation I keep saying i belongs to n f i the same thing. Now, what are you doing you are uniting all the all these sigma algebras. So, f n consist of those subsets. So, f n is the collection of those subsets of omega whose occurrences can be decided in n coin tosses. So, when will this. So, this is another collection of this is also a collection of subsets of omega what kind of elements will it have will contain all those subsets of omega whose occurrences can be decide whose occurrence or non occurrence can be decided in no see I have union over all i countable number see it consist of all those. So, this is something you have to understand f naught consist of all those subsets of omega whose occurrence can be decided in some finite number of tosses. So, why do I say that. So, it looks less though it should you know I deliberately avoid putting infinity in order to not confuse you I equal to 1 to infinity I erase it and put i belongs to n. So, that you do not think of it as f infinity or some such thing is not f infinity f n is those those subsets which can be decided in n coin tosses. So, if. So, let us think of it this way if a subset is contained in f naught it must be contained in 1 of the f i's for some i right. So, it must be decided in some finite i number of tosses. So, it is not something it can be decided in some infinite tosses no right. So, f naught consist.  So, consist of all subsets of omega which can be decided in some finite number of tosses. So, this is the important in some finite number of tosses yes. We take a bit of like intersection like this, but that time it is the same interpretation right it is the. So, if you intersect over a collection index it is the set of all elements contained in all the sets or if it is a union it should be contained in at least 1 of the indices. So, I think you are confusing things that are not related. So, let us just clarify this first. So, I want to make sure that this is clear in everybody's mind. So, if. So, f naught is some collection of subsets of omega right we want to know what kind of subsets are in this f naught. I am saying that if some subset is in f naught let us say if some subset a is in f naught then it must exist in at least 1 of the a i's, but you know that see these f i's are also nested increasing. So, if it is. So, it must be in 1 of the f i's let us say if it is let us say it is in f j. Then it will be in f j f j plus 1 f j plus 2 and so on that is because of the nested structure. So, it consists of all those subsets of omega whose occurrence can be decided in some finite j number of tosses, but the j can be a million or a billion it does not matter right. The j can the j can be as large as you want, but it should be able to call that event in some finite number of tosses it can be very large right. As an example of something if I ask you if the millionth bits the 2 millionth bit or all heads that is a subset in f naught because I can call it looking at the first 2 million bits correct. Can somebody think of an example of something that is not contained in f naught actually very easy all heads all heads right this whether my string is all heads it is all zeros cannot be called looking at f naught correct. Because f naught consists of those events which can be called in some finite number of tosses, but whether it is all heads I have to I can never stop looking at it beyond a point right I mean I have to look at everything right. So, an example of something that is not contained in f naught is whether my sequences all the all head sequence or if I want to answer if all my odd tosses are tails first toss third toss if there are all tails that is what I want to know that is also not contained in f naught correct is that clear. So, good now I want to know what is. So, this f naught I hope everybody understands f naught right. So, now I want to know what kind of an object this f naught is see these f i's are all sigma algebras, but we have to move away from it because it only gives a finite characterization of the first n bits f n gives only a characterization of the n bits. So, we have to move away from it now I will come up with some object f naught which consist of those subsets which can be decided in a finite number of tosses any finite number of tosses. Now, what kind of an object is f naught is the question ok. See if this were an intersection we know that intersection of sigma algebras is always a sigma algebras, but union of sigma algebras need not be a sigma algebras right. So, in fact it turns out that f naught is not a sigma algebras, but it is a algebras you can prove that it is an algebras it is closed under finite unions. So, by which what I mean is that if I have one subset whose occurrence can be called in let us say i tosses and I have another subset whose occurrence can be called in j tosses with let us say j bigger than i then the union of the 2 can be called in the bigger of the 2 j tosses again right. So, it is you can say that it is closed under finite unions, but you can also show that it is not closed under countable union countable infinite unions ok. So, here I go I will put that down. So, we can show that f naught is an algebra and then we can show that f naught is not a sigma algebra. So, this I will leave as a home work this is just chasing up all the definitions right chasing up the definition of an algebra can somebody tell why f naught is not a sigma algebra I just give an example actually right odd let us say odd tosses right. So, let me say for example that let. So, I am just going to prove 2 I am going to prove that it is not a sigma algebra proof of 2 in order to prove that it is not a sigma algebra I can show I can produce an example where it is not closed under countable unions it is closed under finite unions you will show ok. Let a i be the event that the i th toss is a head i th toss is a 0 then and let e equal to the. So, be the event I should not really say event right you know why it is not an event right I have not yet defined the sigma algebra I should say be the subset of omega such that. So, for example a 2 will consist of all those coin tosses all those infinite bit strings in which the second string is a head right similarly a 10 will consist of all those strings for which the 10th is a head right. So, I want to know I want to consider the following e equal to subset of omega such that let us say all let us say all even all even index tosses are heads fine. So, a i so you will know that a i belongs to what f i right a is clearly an element of f i because I can call it in i tosses f i implies a i is a element of f naught for all i correct agree.  So, this much is clear. So, after all a i is whether the i is toss is a head right can be decided in finitely many coin tosses, but I am claiming that my e. So, I can define my e as a countable union of the a i is is not it or .caddle intersection probably is not it true or no. So, if I write e I can write e note that e equal to intersection a i i is equal to 2 4 6 dot dot dot right I am intersecting all the even index a i. So, a i is the corresponds to the ith bit being heads I want all even index tosses to be heads right. So, which means e must be the intersection of all is a i's where the index runs over only the even numbers if you want all your tosses to be heads you will say i equal to 1 through i belongs to n right for example. So, is this clear right I am just mandating that all my even tosses are heads. So, this is all elements of f naught right, but e is not an element of f naught. So, a i belongs to f naught e is not an element of f naught implies f naught is not a sigma. So, I have argued here is for each i a i is an f naught, because whether the ith tosses a head I can decide in finite number of tosses correct which is what f naught is, but e says all my even index tosses must be heads and that is clearly not an element of f naught. Because f naught only consist of those subsets which are decidable in finitely many tosses and I cannot decide e in finitely many tosses, but e is a countable intersection of elements of f naught correct. So, you see the proof. So, here is yet another example of an algebra which is not a sigma algebra. So, just think about this a little bit here I mean I guess it is a little bit easier on the interval and so on right. So, this is a little I am doing this specifically to make you think about this kind of sample spaces as well. So, my f naught is an algebra, but it is not a sigma algebra ok, but there is something nice about an algebra as well right. Yesterday we stated a theorem that says if I tell you the measure on an algebra some pseudo measure on an algebra, then I can extend it under certain circumstances. So, if I tell you the measure measure I would like to put on those subsets which can be decided in finitely many tosses, then may be I can invoke caratheodory and then transfer the measure on to extend the measure on to a sigma algebra. Now, what is the sigma algebra now? Sigma of f naught sigma we do not know what sigma algebra it is some sigma algebra right. So, we can what we will try and do is put a p naught some pseudo measure on f naught then use caratheodory's theorem and extend the measure on to the sigma algebra generated by f naught. Remember f naught is not a sigma algebra. So, you have to make it a sigma algebra by taking countable unions and so on. So, here is the program all right. So, I do the following f naught is not a sigma algebra. So, this is done lemma is done. So, I want to define p naught from f naught to 0 1 satisfying p naught of omega equal to 1 and countable additivity on f naught right. That is what caratheodory wants us to do, but what we should initially do is we have to set our p naught to be right on the algebra in the first place. Just like we did it on the intervals we put p naught's as the length of the interval and then decided we will extend it. Now, we have to say that if you give me an element of f naught which can be decided let us say in n tosses I will basically make all these n 2 power n possibilities equally likely that is what I am going to do to correspond to a uniform measure right. So, we want to define p naught to correspond to fair coin tosses. So, we do as follows let us say I give you a in f naught. So, if a is in f naught.  So, if a is in f naught then it must be in one of the f i's right. Then a is in f i for some i in natural numbers. See you know that if a is in f i it must also be in f i plus 1 and so on right. So, if you want you can put that i for which you can put the smallest i if you want right, but we will see that it does not matter you can take any i because f i's are nested increasing right. So, if you find an i you can also find other i's. So, never mind. So, a belongs to f i some i. So, if a is in f i then what can you say about the first i bits it must be of a certain form right. Then a must be written of the a must have a representation a remember that guy a superscript i must belong to oh wait a second sorry omega. So, I must really write omega 1 omega 2 omega i is in a superscript i is not it this is my characterization of f i. So, I am saying that the first i bit should have a certain pattern well it could be any one of the subsets of 2 power n possibilities right. This a i some subset of 0 1 power n 0 1 power i actually right define I am going to now define the measure define p naught of a is equal to cardinality of a superscript i over 2 power i you see what I am doing. So, this a i will correspond to some pattern among the first i bits in the example I gave i was 10 and I was looking at all those possibilities where there were at least 2 heads remember right. So, in that case my i will be 10 right. So, I want to assign the probability of well p naught which is the pseudo measure as the cardinality of that set. So, what is the cardinality of that set now of the first 10 tosses you want at least 2 heads is what I said. So, you will have 10 choose 2 plus 10 choose 3 plus that will be the cardinality of that set divide by 2 power 2 power 10 in this case. So, that is what I am doing. So, I am again couching it in some notation, but it is actually very simple. So, if for example, to take a very simple example I am looking at the set of all tosses where the third toss is the head. Then I will have it will be an element of f 3 correct. So, I will have 1 by 2 power 3 in the denominator will be 2 power 3 and here the set of a i's will be there are 4 possibilities right you are fixing the third bit, but first you can be anything. So, there are 4 possibilities 4 over 8 half. So, I am basically saying that the probability of some bit being whatever heads or tails is half and I am also saying that if you give me any specific n bit pattern. So, I may be I tell you that my first 10 tosses should be a very specific string. Then there will only be once such thing here and it will be 1 by 2 power 10. So, this is what you would normally call a fair coin toss except now there is an infinite many coin tosses. So, this is perfectly under I mean intuitive it is just couched in some notation. So, is this clear now there is 1 little issue here.  So, I may for example, choose some i which is not the smallest type. Then you may ask me over is this is this measure going to change it will not change come to think of it.  Now, I am looking at 4 strings in which the third bit alone is heads. So, there are 8 possibilities now and the denominator is 16. So, it is again the same as you can verify that in fact, this is this definition of a probability of p naught of a the pseudo measure is independent of whether you actually manage to choose the smallest type or not. So, you let us say you start define saying this is my smallest type, but it does not really matter you can even choose some bigger i this is invariant under choosing bigger i for example. So, this is perfectly well defined uniquely defined. So, this is what I want now I have to verify that p naught of omega what happens to know p naught of omega I have to verify it is 1 is that true. So, we look at p naught of omega then what will be my first i bits will be all 2 power i possibilities. So, it will be 2 power i over 2 power i. So, my omega will consist of all possible binary strings infinite binary strings. Therefore, my first i bits can be all possible 2 power i strings. So, p naught of so clearly p naught of omega is 1. Now, there is in order to invoke karatheodori we need just one more thing. So, you have an algebra f naught you know that p naught of omega is 1 you just need countability over is f naught right now that is non trivial, but it is true. So, now you can invoke karatheodori and say this p naught can be extended into a unique measure on sigma of f naught. So, you can verify p naught of omega equal to 1 this is easy this is 1 p naught is countably additive on f naught this is non trivial it is not trivial, but true therefore, karatheodori holds. So, by karatheodori p naught can be uniquely extended to a measure on what omega comma sigma of f naught extended to probability measure p on omega comma sigma of f naught. And that is my probability measure that is all there is to it and that probability measure will agree perfectly with p naught on this f naught sets right. So, if you ask me under this measure p what is the probability, but my 13th toss is at head it will be half right because p naught says it is half. So, p will agree with it except now this p is also defined on sets like e see remember e was never on f naught e is the event that there all event tosses are heads let us say this e was not in f naught. So, my p naught will not assign any value to it, but my p will be defined on y is now y is p defined on e it is a countable intersection of f naught sets. So, this must be e is not in the algebra, but it is in the sigma algebra. So, p naught is not defined for e, but p is defined for e. So, now what do you think this p of e is half p of e will be 0 try showing that p of e is 0. So, p of e is the p of a countable intersection right you have to use continuity of probabilities. So, do I have running out of time. So, you can write. So, in this case I will just put a little box and give you a hint for this p of e equal to p of intersection i is equal to 2 4 6 dot dot dot a i right. So, this is like a you can write it as i equal to i belongs to 2 n or whatever right. So, you can essentially what you can do may be you can put i equal to 2 i a 2 i may be and put i equal to 1 infinity. So, same thing now what you do. So, this by continuity of probability is limit n tending to infinity probability intersection i equals 1 through n a 2 i right. This is by continuity of probabilities correct there is no nestate decreasing business here, but this is true by continuity of probabilities. Now, what is that 1 by 2 power n right limit of that is. So, this is this guy is you are looking at there are certain n bits have to be heads the probability of that is you know is 1 by 2 power n right. So, this is 1 by 2 power n. So, this will be 0. So, the probability of all even bits being heads is 0. So, that is an example. So, the p naught is not defined for e, but p is defined for e and it is equal to 0 ok. Let us stop here.