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Translating developmental social neuroscience advances into solutions for the early diagnosis of autism spectrum disorder

May 25, 2023
  • 00:02Good afternoon,
  • 00:08Okay. Next week we have a special
  • 00:10speaker coming from Drexel University,
  • 00:12Adam Bemporado, who is the author of a
  • 00:15recent book called A Minor Revolution,
  • 00:18Wonderful book about why we
  • 00:19should be investing in children.
  • 00:21So if you are not sure whether
  • 00:22investing in children is a good idea,
  • 00:24come next week. Further,
  • 00:26if you don't think it's good after today,
  • 00:29you're going to change your
  • 00:30mind because today's talking,
  • 00:31among many other things,
  • 00:32is about investing in children.
  • 00:35So it's a double honor for me today to
  • 00:39introduce today's lecture and lecturer
  • 00:42and my what a what a pairing we have.
  • 00:45So today is the Donald Cohen
  • 00:47Memorial Lecture as we sit here
  • 00:50in the Donald Cohen Auditorium,
  • 00:52many of us.
  • 00:53Got to know Donald as a great scholar,
  • 00:57leader in the in many fields developmental
  • 01:00psychopathology and autism particularly
  • 01:02relevant today and and also as an
  • 01:05incredible mentor to many of us,
  • 01:07Linda Mays,
  • 01:08Andres Martin and our speaker included.
  • 01:13So there's the Donald Cohen angle to
  • 01:17today's talk and then of course there's
  • 01:20the Ami Clinton angle to today's talk.
  • 01:22Many of us know and yes,
  • 01:25love Ami Klin and have for many years.
  • 01:28Ami was here between 1989 and 2010,
  • 01:33so he had a long run here at the Child
  • 01:36Study Center and then 12 years ago.
  • 01:39Alas for us and oh fortune for Atlanta,
  • 01:44he was recruited as the founding director
  • 01:47of the Market Center for Autism, which is.
  • 01:50Just an unbelievable creation that
  • 01:53you're going to be hearing about today.
  • 01:57Ami is originally from Brazil.
  • 02:01His schooling was both in Brazil than in
  • 02:04Israel and ultimately his PhD in London.
  • 02:08When we were reminiscing paying
  • 02:11his debt for his PhD studies,
  • 02:14he worked as a delivery boy in
  • 02:18a motorcycle through London.
  • 02:20And I think that the back of the
  • 02:22thing read anything, anywhere,
  • 02:25anytime, anything to any to anywhere.
  • 02:29And thus a great career was born.
  • 02:32When Donald saw this spectacle,
  • 02:35he said you are not going to endanger that
  • 02:38brain of yours with or without a helmet.
  • 02:40This must stop.
  • 02:41And Donald brought on me to New Haven and
  • 02:45a great, great, great career was born.
  • 02:49And I'll.
  • 02:51I'll let Ami tell things,
  • 02:54but I want to just add one thing.
  • 02:56Someone said, and I'm not sure who did,
  • 02:58but someone said that beauty is
  • 03:01the reflection of truth.
  • 03:03Bob King, do you know who said that?
  • 03:06Well, OK, so Bob King doesn't know,
  • 03:09so it's unknown.
  • 03:09But someone said that.
  • 03:12Let me repeat that beauty
  • 03:14is the reflection of truth.
  • 03:16And when I've seen Ami's studies and papers,
  • 03:19this is true.
  • 03:22His science is beautiful.
  • 03:24So his science is so beautiful.
  • 03:26You want to frame it in your living room.
  • 03:29You want to eat it.
  • 03:30It's delicious. It's beautiful.
  • 03:32But it's not just beautiful to the eye.
  • 03:35It engenders deep truths,
  • 03:37deep truths that through all of these
  • 03:40incredible titles and positions
  • 03:42and platform that Ami now has.
  • 03:45He is taking to the city of Atlanta,
  • 03:46to the state of Georgia
  • 03:48and indeed to the world.
  • 03:50And we are all the more fortunate for it.
  • 03:52So Ami via Manila, La Casa.
  • 03:54Welcome back home.
  • 03:54Love having you,
  • 04:04Andres. Thank you.
  • 04:07This is, this is home away from home.
  • 04:09Actually, this is, this is,
  • 04:11this is the home I grew up,
  • 04:14certainly intellectually.
  • 04:15Thank you for just very,
  • 04:17very generous introduction.
  • 04:19The fact is that I owe,
  • 04:21I owe my my, my intellectual,
  • 04:24my professional career,
  • 04:25my clinical career to everything
  • 04:27that happened between those years
  • 04:29that you've mentioned and some of
  • 04:31those giants that I was influenced by
  • 04:33are sitting right now in this room.
  • 04:35And so thank you, thank you,
  • 04:37thank you, thank you,
  • 04:38thank you for everything that you've
  • 04:41done so for me being in this hall.
  • 04:45Is Needless to say, is very emotional.
  • 04:48There are some very important
  • 04:49people that influence my life.
  • 04:51You mentioned Donald.
  • 04:52Donald, yes.
  • 04:54I was the only dispatch writer
  • 04:56in London with a PhD and and
  • 04:59meeting him at Swiss Cottage,
  • 05:01he went beyond the way that I was dressed
  • 05:04and obviously did thanks to the larger.
  • 05:06So she's hot and you could see that
  • 05:08maybe there was some potential
  • 05:10and that I could come here.
  • 05:11But he has been present in
  • 05:13our lives every day.
  • 05:14And I cannot thank him for all that
  • 05:18he's done on my behalf of the years.
  • 05:21There are others that I would
  • 05:24like to briefly remember.
  • 05:26Dom and Sarah. They adopted me.
  • 05:29They held my American wedding in
  • 05:33their house and they cooked for it.
  • 05:35And I miss them.
  • 05:37I miss them really badly.
  • 05:39And then there are the folks that
  • 05:41I work for a long, long, long,
  • 05:43long period of time in the trenches
  • 05:46and I need to thank them too.
  • 05:48Fred is not here,
  • 05:50but I owe,
  • 05:51I owe tremendous thanks to Fred for
  • 05:54allowing me to share 20 years of his
  • 05:58clinical life and that has been tremendous.
  • 06:01And then Warren Jones
  • 06:04somebody that I've been.
  • 06:06Collaborating with for the past
  • 06:092223 years right here at the
  • 06:12CDU 1st and everything that I'm
  • 06:14going to present to you today is
  • 06:17a cocreation with Warren Chance,
  • 06:20OK Disclosures.
  • 06:22This presentation includes research
  • 06:24related to investigational
  • 06:26device development.
  • 06:27Warren and myself are Invent
  • 06:29Inventors patent holders.
  • 06:31This has been licensed to this company
  • 06:32called Early Tech Diagnostics,
  • 06:34which evaluates medical technologies
  • 06:36and hopefully provides revenue to
  • 06:38support treatment of children with autism.
  • 06:40This external activity is monitored
  • 06:42by the Dean at Emory University
  • 06:45School of Medicine and off we go.
  • 06:47Autism is a huge public health challenge.
  • 06:52You'll know one in 36 is the most
  • 06:55common complex near developmental condition.
  • 06:58And I like to to think in terms of
  • 07:01the fact that 95,000 children will
  • 07:03be born this year who will have autism.
  • 07:07It's enormous societal cost,
  • 07:09but most importantly an enormous economic
  • 07:12burden to the individual families.
  • 07:15The good news is that early
  • 07:18diagnosis and early.
  • 07:20Intervention and support can optimize
  • 07:23outcomes that are going to make a
  • 07:27difference in this children's lifetimes.
  • 07:30And here is the not so good thing,
  • 07:32Even though we've learned for the
  • 07:34past 20 years and the American
  • 07:36Academy of Pediatrics has recognizes
  • 07:37at least from
  • 07:382007, the median age of diagnosis of
  • 07:41autism in this country is still late around
  • 07:444:00 to 5:00 and a half, and even later.
  • 07:48For low income families,
  • 07:50for minority families, and to rural
  • 07:53in families from rural communities.
  • 07:55And one of the things contributing
  • 07:57to this challenge is the fact that we
  • 08:00don't have a lot of cautions in life.
  • 08:02We don't have a lot of Jamie's in life,
  • 08:04We don't have many extra clinicians.
  • 08:06So in the community,
  • 08:08Oh my God, so good to see you
  • 08:13Kyle. What a pleasure.
  • 08:15I'm sorry, I just saw you sitting here.
  • 08:18OK, good to see you.
  • 08:21We don't have a sufficient
  • 08:23number of clinicians.
  • 08:24Therefore, out there in the community,
  • 08:27families may wait years and years in
  • 08:30order to see and to get a diagnosis.
  • 08:32And you need a diagnosis in most
  • 08:34situations in order to access services.
  • 08:36So autism is a public health challenge,
  • 08:38is also a public health opportunity.
  • 08:40This is what we've learned
  • 08:42in the past 20 years or so.
  • 08:44Autism is the most strongly genetic of all
  • 08:47complex neuro developmental conditions.
  • 08:49If I have a child of autism,
  • 08:51as you all know, my the younger child,
  • 08:54one to two and five will also have autism.
  • 08:59But the problem is of course,
  • 09:01that the genetics of autism
  • 09:03is enormously complex.
  • 09:05There are hundreds and hundreds of
  • 09:07genetic variants that have already been.
  • 09:09Implicated in autism.
  • 09:10And yet you don't go from genes
  • 09:12to the symptoms of autism.
  • 09:14And here is the hypothesis is that
  • 09:18genetic liability actually disrupts.
  • 09:20And Kyle,
  • 09:21you would recognize something
  • 09:22that you've contributed and
  • 09:24thank you very much for training.
  • 09:27Me too.
  • 09:28Genetics,
  • 09:29actually,
  • 09:30that liability disrupts normative
  • 09:32development and and autism
  • 09:35becomes really the results of the
  • 09:38disruption of normative development.
  • 09:40And for that I need to start
  • 09:42from the beginning.
  • 09:43And the beginning is that babies are
  • 09:46born in the state of utter fragility.
  • 09:49If babies were left by themselves
  • 09:51they would die.
  • 09:52So God or nature made sure that
  • 09:54this would not happen and and so
  • 09:57babies when they are born anything
  • 10:00in their surroundings that is going
  • 10:02to sound like give us or smell or
  • 10:05move or look or interact like give
  • 10:08us is going to command the attention
  • 10:12of newborns and and biology such
  • 10:16that everything happens in past.
  • 10:18And so in the same way that babies
  • 10:21are oriented to the caregivers,
  • 10:23caregivers of course are engaged
  • 10:25with their babies.
  • 10:26And it's out of this mutually reinforcing
  • 10:30choreography that brain moves forward.
  • 10:32And that's a very important concept.
  • 10:35In fact,
  • 10:35these are the three concepts
  • 10:37that I want to make sure these
  • 10:39are coonesque set of concepts.
  • 10:42They are Kyle Esque.
  • 10:44Or they are Sally Prevention.
  • 10:46I don't know how do you do that,
  • 10:48Kyle,
  • 10:48but all of these are concepts that
  • 10:50have been near and dear to most
  • 10:52of us working with young children.
  • 10:54In this building #1 babies are
  • 10:56born to socially Orient.
  • 10:58Second,
  • 10:59what moves brain forward is
  • 11:02reciprocal social interaction.
  • 11:04Simply placing a child in front
  • 11:06of television is not going to
  • 11:08make the child speak.
  • 11:09You need a somebody on the
  • 11:11other side engaging that baby.
  • 11:13Reciprocal social interaction.
  • 11:14And the third concept, of course,
  • 11:17is the one of neuroplasticity,
  • 11:19because this is the first two years of life,
  • 11:22is the period of maximal
  • 11:25neuroplasticity for our lifetimes.
  • 11:28By the time that we celebrate
  • 11:30the baby's 1st birthday,
  • 11:31that baby's brain has doubled and
  • 11:34synaptic density has quadrupled.
  • 11:36Really beginning to reposit.
  • 11:38Those early experiences that
  • 11:41babies have
  • 11:42from the first days and weeks of life.
  • 11:46So in many different ways,
  • 11:47how state is more than once to date.
  • 11:50Brain structure and function is the physical
  • 11:53instantiation of those early experiences,
  • 11:56and we need to remember that.
  • 11:58OK, So what about autism then?
  • 12:02Kasha wrote at least two papers that
  • 12:04I remember on parental concerns.
  • 12:07So parents are concerned about their
  • 12:08children from very, very early on.
  • 12:10But it takes years for parents
  • 12:13to access experts who will be
  • 12:15able to diagnose the child.
  • 12:18And that diagnosis is typically the
  • 12:21ticket to early intervention, to early
  • 12:23treatment in support of the families,
  • 12:25the median age I already mentioned.
  • 12:27But the issue is this is an issue of access.
  • 12:30There are not many child
  • 12:31study centers in this country.
  • 12:32In fact, there are not many
  • 12:34specialized centers in this country.
  • 12:36Remember, 95,000 children are
  • 12:39born every year who have autism.
  • 12:41So this is the work that we've
  • 12:43been trying to sort of to advance.
  • 12:46We need to go, We don't want to replace,
  • 12:49As for clinicians,
  • 12:50people like even myself,
  • 12:52but we need to to give
  • 12:54greater access to families,
  • 12:55to high quality diagnostic services
  • 12:57so that the children can be treated.
  • 12:59We need to use biomarkers,
  • 13:02they need to be objective
  • 13:04and quantitative dimension.
  • 13:05They need to be standardized.
  • 13:07They need to be cost efficient so that
  • 13:09we can scale them and they need to be.
  • 13:11And we need to be able to capture
  • 13:13the core features of the condition
  • 13:15so that when we are devising
  • 13:17treatment plants that we are focusing
  • 13:19on those things that are pivotal
  • 13:21milestones for children who are
  • 13:22going to push forward speech,
  • 13:24language and communication
  • 13:26and cognition and so forth.
  • 13:29So we have Warren and I have been
  • 13:31using this technology called eye
  • 13:33tracking for quite some time.
  • 13:35But the concept that we try to measure is
  • 13:37the concept of social visual engagement,
  • 13:40which is basically the way we look
  • 13:43at and learn about the world.
  • 13:45So imagine social visual engagement
  • 13:48in babies will be.
  • 13:49What they are looking at and learning
  • 13:52about in their immediate social environment,
  • 13:56and here is just an example.
  • 13:57So you see that cross there.
  • 13:59That cross is basically a toddler
  • 14:02looking at this two toddlers
  • 14:04interacting K and you can then measure
  • 14:08120 times a second moment by moment
  • 14:12how that toddler is hi waiting,
  • 14:15the perception of that experience that
  • 14:17is happening right in front of them.
  • 14:19So it's a Co creation.
  • 14:21That's why we talk about
  • 14:23transactional biomarkers,
  • 14:24because what's being created
  • 14:25is not only on the baby side,
  • 14:28it's not only on the other,
  • 14:30it's actually the mutually reinforcing
  • 14:32choreography between the two is that
  • 14:36baby creates an experience that is
  • 14:38what's happening in front of them,
  • 14:40a transactional biomarker, OK.
  • 14:42So,
  • 14:42but one of the big sort of technical
  • 14:45problems that we've sort of
  • 14:47encountered is how do you quantify
  • 14:49social visual engagement particularly
  • 14:50for groups of people.
  • 14:52And so we started this way,
  • 14:54this is what we want and see if it
  • 14:59so this is the battleground
  • 15:01of brain development in tops.
  • 15:13I die for your thoughts. Here we go.
  • 15:19This is how children learn about paying
  • 15:22attention to people's faces and facial
  • 15:24expressions and nonverbal gestures.
  • 15:26And and and communication and and
  • 15:29and and maybe calling somebody
  • 15:31else in conflict with such.
  • 15:33I mean, you name it,
  • 15:34This is what we want to know.
  • 15:36How does a child create?
  • 15:39An experience out of the simulator
  • 15:40that I just put in front of you.
  • 15:42So this is what we did.
  • 15:44This is a frame of video,
  • 15:45the 30 frames per second.
  • 15:47And then we basically measure a say a
  • 15:502 year old one child looking at that
  • 15:53frame of video at that moment in time.
  • 15:56And what you see there is an equation
  • 15:58and that equations basically shows the
  • 16:00amount of visual resources that that
  • 16:03toddler is dedicating to that point
  • 16:04of the screen at that moment in time.
  • 16:07And that equation comes from the mapping
  • 16:10of photoreceptive cells in in primate eye.
  • 16:13OK, Now if you have 45 two year olds
  • 16:17looking at that frame at that moment in
  • 16:19time and they're looking at the same spot,
  • 16:21what you see is that the colors
  • 16:23are getting hotter, OK,
  • 16:24And that means that there is a convergence
  • 16:27of attention across all these children.
  • 16:29Remember,
  • 16:30there is a frame of video there.
  • 16:31Now let's take a different
  • 16:33kind of perspective.
  • 16:34Let's take the bird's eye view of that frame,
  • 16:37and what you see in front of you now is
  • 16:39something that we've called a salience map.
  • 16:42And what you see is that the hot color,
  • 16:44like the Reds,
  • 16:45means that more children are converging
  • 16:48attention on and the Blues you don't
  • 16:50see many children paying attention to.
  • 16:52And now what you can do is to basically
  • 16:55watch the same video that I showed you
  • 16:58before through the eyes of 45 two year olds.
  • 17:01And you see that this is
  • 17:03changing all the time.
  • 17:04Sometimes it is is dispersed,
  • 17:06but sometimes something really
  • 17:07important happens in middle of the
  • 17:09screen or in the side of the screen
  • 17:10and they all going to focus on that.
  • 17:12And we were sort of fascinated by the
  • 17:15fact that when we're doing this work
  • 17:18with typically developing toddlers,
  • 17:20they would watch our videos and
  • 17:2180% of the time they'll be looking
  • 17:23at the same spot at the same time.
  • 17:25And so these are what a wonderful child
  • 17:29psychologist from Seattle One said.
  • 17:31This is a hotspot of socialization.
  • 17:34So Andy Meltzer decided to name it
  • 17:36this way because this is a momentary
  • 17:38thing that happens in front of the
  • 17:41child that all children will focus
  • 17:43on because they're all entrained
  • 17:45to that hotspot of socialization,
  • 17:48something they need to learn.
  • 17:50In order to understand social interactions,
  • 17:53OK, let's take a different perspective.
  • 17:55Now let's bring in another axis.
  • 17:58And this axis here is the axis of time.
  • 18:01And what do you see are lots of frames,
  • 18:03the frames of the videos.
  • 18:05Now let's take that salience map
  • 18:07and let's carve it
  • 18:09all the time. OK, And So what you
  • 18:12have now is a space-time distribution,
  • 18:14and when he gets red, when he gets hot.
  • 18:18It means that this is something that
  • 18:20we've called an attentional funnel.
  • 18:23Basically children are looking at
  • 18:24different spots and that all of a
  • 18:27sudden something important happens
  • 18:28and there is a funneling of the
  • 18:30attention of all of these children.
  • 18:32And now what you can do is to watch this
  • 18:35video that I showed you through the funnel.
  • 18:38It basically that funnel right here is,
  • 18:42is is basically encircling.
  • 18:44What is really important for these
  • 18:47children as they are going through
  • 18:50that particular video now let me
  • 18:53just show you here as you see.
  • 18:57Right here, they're not looking at
  • 19:00the faces of those two toddlers.
  • 19:02They are looking at something that
  • 19:04is in between those two children.
  • 19:06And that's the object that they
  • 19:08are fighting over.
  • 19:09Because all of those two year olds
  • 19:11were able to grab the gay skew that
  • 19:13comes from one of the toddlers,
  • 19:15and they are focusing on the object
  • 19:18of shared attention.
  • 19:19And this is happening in
  • 19:22intensive milliseconds.
  • 19:23OK, so keep that in mind now.
  • 19:26This is now.
  • 19:27What we call a normative funnel of
  • 19:31attention as all of these typically
  • 19:33developing 2 year olds are traversing
  • 19:35that particular frame of video.
  • 19:37OK,
  • 19:37and so now what you see are skin paths of
  • 19:42two year olds of autism traversing the same.
  • 19:45The same frame,
  • 19:47and this is what the typically
  • 19:49developing children are focusing on.
  • 19:51And this is what the children
  • 19:52with autism are focusing on.
  • 19:54So they are exposed to exactly the same,
  • 19:57the same stimuli, OK,
  • 19:59those toddlers playing,
  • 20:00but they Needless to say,
  • 20:02they are reconstructing internally
  • 20:04a very different experience.
  • 20:07And what we found out is that those
  • 20:10things happen hundreds and hundreds
  • 20:12of time within 5 minutes of free
  • 20:15viewing of a video like that.
  • 20:18To the extent that we could
  • 20:20measure that our our kids,
  • 20:21the ones with autism,
  • 20:22the two year olds of autism,
  • 20:24were diverging over 570 times from
  • 20:27the experience of their peers.
  • 20:30Now this was happening in 5 minutes.
  • 20:32They are not only diverging
  • 20:34during our experiments,
  • 20:35they are diverging in their lives.
  • 20:37And so if you extrapolate,
  • 20:39imagine thousands of missed
  • 20:42opportunities of social learning,
  • 20:45OK, in a few hours,
  • 20:47and really millions in the
  • 20:48first two years of life.
  • 20:49So this is our conception of autism.
  • 20:52If you miss thousands and thousands
  • 20:54and thousands of opportunities
  • 20:56for social learning,
  • 20:58you will become socially disabled.
  • 21:00OK, now remember that.
  • 21:07These are the experiences that the
  • 21:10children may be having on in their lives.
  • 21:13And if we go by Joe Le Doux's
  • 21:16sort of subtitle of a great book,
  • 21:18that our brains become who we are,
  • 21:20those early experiences are basically
  • 21:23becoming the brains of the children.
  • 21:27That's the reason I meant that the
  • 21:30brain becomes a physical instantiation
  • 21:32fact of those early experiences.
  • 21:35Now this biomarker social visual
  • 21:37engagement has become very important
  • 21:39to us. We needed to show first of all that
  • 21:41he was a biomarker and what we found out.
  • 21:43This is work with our good friend
  • 21:46John Constantino and just.
  • 21:48So we did studies with twins, OK?
  • 21:51And what we found out is that
  • 21:54something as ephemeral as eye looking.
  • 21:56You know, eyes are very important
  • 22:00false mechanism of socialization.
  • 22:01The eyes are not only the window to the soul,
  • 22:05they're the window to to the social brain.
  • 22:09So much so that the more,
  • 22:11say an animal needs caregiving,
  • 22:15the greater the contrast of the sclera.
  • 22:18So, for example, primates have sclera,
  • 22:20humans have most of all,
  • 22:22but a rodent like a chinchilla does not.
  • 22:24That's not the way that
  • 22:26caregiving happens with rodents.
  • 22:27So eyes are very important.
  • 22:29So just thinking in terms of eye looking,
  • 22:31when we had twins that were basically
  • 22:34watching videotapes in two separate rooms.
  • 22:37OK, identical twins,
  • 22:39MZ twins and fraternal twins,
  • 22:42DZ twins.
  • 22:42What we found out is that social visual
  • 22:45engagement is very strongly influenced
  • 22:47by genetic variation with a heritability
  • 22:50of over 90% in fact .91 in this study.
  • 22:54And so the concordance rates
  • 22:56for identical twins was .91,
  • 22:59for fraternal twins it was only .35,
  • 23:02and for just the age and sex
  • 23:05match was only .15,
  • 23:07so under strong genetic influence.
  • 23:10And interestingly,
  • 23:11those highly heritable assays were also the
  • 23:14assays that were separating the children,
  • 23:17the tablets of autism,
  • 23:18you know,
  • 23:19the most efficiently from their
  • 23:21typically developing peers in
  • 23:23one cohort and in another cohort
  • 23:26in a replication cohort now.
  • 23:28What to us was remarkable is that
  • 23:32that genetic control of social
  • 23:34visual engagement was not only on
  • 23:36measures that were summary measures,
  • 23:38like I looking over a period of time
  • 23:40that a child was actually watching a video.
  • 23:43It was moment by moment to the extent
  • 23:46that identical identical twins,
  • 23:48they were more likely than fraternal
  • 23:50twins to shift their eyes.
  • 23:52At the same moment,
  • 23:53in the same direction,
  • 23:55onto the same semantic targets and
  • 23:57microscales of 10s of milliseconds.
  • 24:00So we are really talking about two
  • 24:02synapses from retina.
  • 24:03So this is the extent to which
  • 24:06God or nature decided,
  • 24:08going along with Kyle and Donald,
  • 24:10that we are born social beings,
  • 24:13we are the product of our relationships
  • 24:16and nothing has shaped really nothing
  • 24:18has shaped the primate brain as much.
  • 24:22As sociality.
  • 24:23OK, so this is now what Warren did here.
  • 24:28Even though the twins watched those
  • 24:30videos in different in different rooms,
  • 24:32Warren brought together their eye
  • 24:34tracking signal which is this
  • 24:36crosshair from 2 videos onto the same.
  • 24:39So this is now fraternal twins
  • 24:42watching this video.
  • 24:43You can see the concordance.
  • 24:45Remember they are watching this
  • 24:47video in different rooms
  • 24:50and now. These are identical twins
  • 24:53watching this video in different rooms.
  • 25:01So an agreement of .91.
  • 25:05Well, how early does that assay begin
  • 25:10to segregate children of autism from
  • 25:13their typically developing peers?
  • 25:15This is now in slow motion,
  • 25:18a typically developing 5 months
  • 25:20old looking at the caregiver
  • 25:23falling in love with her eyes.
  • 25:25And this is a 5 month old who
  • 25:28was later diagnosed with autism.
  • 25:31A very different way of looking
  • 25:34at that speaking face, now over 3.
  • 25:39Cohorts, we follow children from the age
  • 25:42of two months to the age of 24 months.
  • 25:45Densely sample collecting eye tracking
  • 25:47data monthly until six months and
  • 25:49every three months thereafter.
  • 25:51And what we are able to see is
  • 25:53that this in blue here is the
  • 25:56growth chart of eye looking for
  • 25:58typically developing children.
  • 26:00You see it goes up, down and up,
  • 26:03up, OK and this goes from
  • 26:05two months to 24 months.
  • 26:07For the children who are later
  • 26:09diagnosed with autism over 3 cohorts,
  • 26:11they start over here and it's free
  • 26:14fall for the first two years.
  • 26:16So this is autism unfolding
  • 26:18right in front of your eyes.
  • 26:20We have differences in the first
  • 26:22six months that are predictive of
  • 26:25diagnostic classification as well
  • 26:27as level of disability at the ages
  • 26:30of 24 and 36 months experiences in
  • 26:32the first six months of life. OK.
  • 26:34Another thing that we found out,
  • 26:36everything that we do with human infants,
  • 26:38we do with infant monkeys because
  • 26:40they are an extraordinary platform
  • 26:42for studying the social brain.
  • 26:44So with colleagues at the Emory
  • 26:45Primate Center,
  • 26:46John Celine by Chevalier and Marsanches,
  • 26:48what you see here is basically
  • 26:51I'm looking in both human infants
  • 26:53from 2 to 24 months,
  • 26:55and here you seen black infant monkeys.
  • 26:58And you need to do a transformation.
  • 27:00You need to divide by 4 because monkeys
  • 27:03mature much more quickly, of course.
  • 27:05But you see that the pattern
  • 27:07of I looking is very similar.
  • 27:09It serves the same adaptive value.
  • 27:11This assay is highly phylogenetically
  • 27:14conserved.
  • 27:15So that's the reason why we're
  • 27:17excited about this biomarker.
  • 27:18But could we use it?
  • 27:21To provide greater access to
  • 27:23early diagnostic services.
  • 27:24So this is what we did.
  • 27:25We took some of this lab and gosh,
  • 27:28I might remember this lab well.
  • 27:30And then we started building
  • 27:31a prototype of something that
  • 27:32would be more portable somebody,
  • 27:34something that could actually
  • 27:35be deployed in the community.
  • 27:36And we ended up with with this
  • 27:39prototype and here is what it
  • 27:41looks like these days.
  • 27:47It's just like the car,
  • 27:48it's just like the cars
  • 27:52hanging in here,
  • 27:57so it's entirely automated.
  • 27:58The whole idea is to make it
  • 28:01as efficient as possible so a
  • 28:04minimally trained technician can
  • 28:07actually perform this procedure.
  • 28:09So this is what the the technician does
  • 28:12while the child is inside watching.
  • 28:18This calibration is automated,
  • 28:19but this is what the child sees. OK,
  • 28:28and
  • 28:32that's the end.
  • 28:33He did such a good job.
  • 28:37So we built this prototype in
  • 28:40order to conduct some studies,
  • 28:43and these studies would make use
  • 28:46of this quantification procedure.
  • 28:48Our follows of attention what
  • 28:49we what we did is that we create
  • 28:52large bodies of normative data
  • 28:54for looking behavior and typically
  • 28:56developing children as they watch
  • 28:58all these things so that we would we
  • 29:01could create this moment by moment
  • 29:03normative benchmark against which we
  • 29:05could compare individual children
  • 29:06And the the first aim of this work
  • 29:10was to derive quantitative indices
  • 29:13for the classification of autism.
  • 29:16And so as you see here, the children,
  • 29:18each individual child diverges from
  • 29:21that normative benchmark hundreds of times,
  • 29:24hundreds if not thousands of times.
  • 29:26Within the context of this procedure is
  • 29:29about between 8:00 and 12:00 minutes.
  • 29:31And so we would mind this thousands
  • 29:33of divergences, as it were,
  • 29:36in order to create a.
  • 29:38A diagnostic classifier, OK,
  • 29:39And the diagnostic classifier is
  • 29:41always going to be the reference standard,
  • 29:44the gold standard.
  • 29:45So expert clinicians conducting the
  • 29:48diagnosis independently of course,
  • 29:50from this experimental procedure.
  • 29:51But we wanted to do a little more as well,
  • 29:54because for those of us who do
  • 29:57those diagnostic evaluations,
  • 29:58it's not only the diagnosis.
  • 30:01Autism is a huge spectrum is
  • 30:03very critical for us to have at
  • 30:05least three additional measures.
  • 30:07One is the level of autism or
  • 30:08the level of social disability
  • 30:10typically measure with the Ados,
  • 30:12the Autism Diagnostic Observation Schedule,
  • 30:14as well as the level of verbal
  • 30:16learning and nonverbal learning
  • 30:18and that of course coming from the
  • 30:20Mullen Early Scales of learning.
  • 30:22We wanted to be able to derive that too.
  • 30:26So we conducted 3 studies.
  • 30:27The first one packaged in,
  • 30:30one we call the feasibility trial,
  • 30:32had a discovery sample and
  • 30:35a replication sample.
  • 30:36And then there was a pivotal,
  • 30:37a national pivotal trial.
  • 30:39The goal we focus on 16 to
  • 30:4130 month old children,
  • 30:43primarily because of the
  • 30:46the the federal mandate,
  • 30:47the Part C services,
  • 30:49the early division services that
  • 30:50most of the children don't access to
  • 30:52because they don't get a diagnosis.
  • 30:54So we prioritize the age of 16 to 30 months.
  • 30:57We wanted to know if this
  • 31:00would accurately assess autism.
  • 31:02Proxy in fact the diagnostic process
  • 31:04executed by an expert clinician
  • 31:07and we wanted to see the extent to
  • 31:10which we could create those those
  • 31:12measures of severity proxying anaidas
  • 31:14and the two measures of the moment.
  • 31:17The the discovery sample was over
  • 31:22700 children primarily at Marcus.
  • 31:25And the replication sample was
  • 31:29370 toddlers and one was at Wash
  • 31:31U with my friend John Constantino
  • 31:34and the other part of it was in
  • 31:38a community Health Center about
  • 31:4050 miles north of of of Atlanta.
  • 31:42We wanted to we want to see does this
  • 31:45work in the real world K not in the lab.
  • 31:48And then the second study was a
  • 31:51pivotal trial national clinical
  • 31:53trial with 335 toddlers.
  • 31:55And we conducted that as Seattle Children's,
  • 31:57Cincinnati Children's, UCSF,
  • 32:00Rush Phoenix and Emery Ki.
  • 32:04Know this is a little small,
  • 32:06but this is from the visibility study.
  • 32:09This is the discovery data
  • 32:11and the replication data,
  • 32:13the clinical characterization sample.
  • 32:15And what you see here is that the
  • 32:18kids were around 21 to 24 months.
  • 32:21They represented the full spectrum.
  • 32:23Of social disability through the Atos
  • 32:25and the full spectrum of verbal and
  • 32:28nonverbal ability using the Mullin.
  • 32:30So some children were severely delayed,
  • 32:32but some children are actually precocious.
  • 32:34And this is the clinical characterization
  • 32:37sample for the national trial And
  • 32:39you see here the classification
  • 32:42was autism versus not autism.
  • 32:45It was not autism versus typical.
  • 32:47OK, so of the 185 toddlers
  • 32:51with non autism diagnosis.
  • 32:5487.6% had other non autistic
  • 32:57developmental delays,
  • 32:58only 13 kids had no diagnosis.
  • 33:01And of the $150.00 of Voltas and 42.7%
  • 33:06did not have developmental delays.
  • 33:08OK, so we had the full spectrum on
  • 33:12both sides and here are the results.
  • 33:15Ignore the discovery study because
  • 33:17this is where we develop our mode.
  • 33:20This is where develop our.
  • 33:22Our mathematical model,
  • 33:24but in the replication sample,
  • 33:27the diagnostic classifier was able,
  • 33:29we're able to achieve over
  • 33:3180% of sensitivity,
  • 33:32specificity,
  • 33:33positive predictive value and negative
  • 33:36predictive value and and and those
  • 33:39numbers were fairly replicated in the
  • 33:42national in the national clinical trial.
  • 33:45What about our indices of severity?
  • 33:48Remember that the ADAS,
  • 33:50the higher the number on the ADAS,
  • 33:52the more socially disabled you are and
  • 33:55it's different in our eye tracking metric.
  • 33:57That's why you have this direction here.
  • 34:00But on the replication,
  • 34:01say for example,
  • 34:02we're able to capture 72% of the variance
  • 34:06of ADA scores in that 8 to 12 minute
  • 34:10procedure and in the national clinical trial.
  • 34:14About 74% of that variance.
  • 34:17OK,
  • 34:18so you remember takes,
  • 34:21it takes a well trained person to do aid us,
  • 34:23a well trained person to do the Mullen.
  • 34:25It takes a long time to complete that.
  • 34:27What about the verbal ability
  • 34:28on the replication sample,
  • 34:30we're able to capture 58% of the variance
  • 34:35and 65% of the variance of verbal
  • 34:39ability and for nonverbal ability.
  • 34:42About 64% of the data.
  • 34:44So we are very happy with those results.
  • 34:48But we needed to make sure particularly
  • 34:50if you're dealing with FDA that you
  • 34:53need to conduct studies that are called
  • 34:55repeatability and reproducibility.
  • 34:56So you need to quantify measurement
  • 34:59precision, measurement error.
  • 35:01So you need to put children through
  • 35:03this ordeal which is the same child
  • 35:06needs to complete the the procedure
  • 35:08three times on the same device.
  • 35:11And then three times again across devices,
  • 35:13OK, measure,
  • 35:14these are the infamous RNR studies,
  • 35:17but the data are good.
  • 35:19So that we could see that repeatability
  • 35:22and representability variance was
  • 35:24accounting for very little of
  • 35:26what we've got and most of the
  • 35:29variance really was due to between
  • 35:32subject participant variance.
  • 35:34So we are very,
  • 35:36very happy with.
  • 35:38This low measurement error
  • 35:39because it gives us more precision
  • 35:41what we do. And if I combine all of the
  • 35:44studies together this is this is the data.
  • 35:47These are the sensitivity, specificity,
  • 35:50PPV&PV and accuracy of the device
  • 35:52right now and and here are the the
  • 35:56amount of variance that they are
  • 35:58capturing of social disability.
  • 36:00The aid us verbal ability to Mullen,
  • 36:03nonverbal ability from the Mullen as well.
  • 36:05So how can I summarize this?
  • 36:08Happy that we got high sensitivity
  • 36:11and specificity when comparing those
  • 36:13eye tracking assays with expert
  • 36:17clinician diagnosis with sensitivity
  • 36:21and specificity and PPV&NP V / 80%.
  • 36:24And very happy that they are also capturing
  • 36:27large variances of those indices.
  • 36:29Those reference standard indices
  • 36:32of severity and the goal here is
  • 36:36never to replace the clinician.
  • 36:38The goal here is to free the
  • 36:40clinician to spend more time with the
  • 36:42parents so that we can do what the
  • 36:45diagnostic process is supposed to be.
  • 36:47Is only supposed to be a window to treat.
  • 36:50So we need to make sure that clinicians have
  • 36:52more time to spend time counseling a family,
  • 36:55supporting the family,
  • 36:56and most importantly,
  • 36:57doing the care coordination so that
  • 37:00we can translate diagnostic results.
  • 37:02Into actual treatment.
  • 37:04So the good news about this procedure
  • 37:08is that this was done under FDA
  • 37:13sort of rules for past 6-7 years
  • 37:16and they cleared this device as a
  • 37:19clinical tool since June of last year.
  • 37:23So this is now a clinical tool which is very,
  • 37:27very, very exciting.
  • 37:29The idea is to support a public
  • 37:31health system that does not have
  • 37:33enough extra clinicians.
  • 37:35The idea is to deploy tools that are
  • 37:38cost effective and will increase access,
  • 37:40particularly for those families
  • 37:42that are marginalized,
  • 37:44particularly low income minority
  • 37:46and rural families.
  • 37:48Autism.
  • 37:48Well, it's it's the same in most healthcare,
  • 37:52but in autism in particular,
  • 37:54the healthcare disparities are stark.
  • 37:57If you are a black child
  • 37:59with autism in this country,
  • 38:00you are at double the risk of
  • 38:03intellectual disability than a white
  • 38:04child with autism in this country.
  • 38:06And that is so not because, believe me,
  • 38:09we have a whole grant with our our,
  • 38:12our colleagues at UCLA and Wash
  • 38:14U and what not.
  • 38:16It's not the genetics,
  • 38:17it's really the access is those
  • 38:19early experiences that those
  • 38:21families are being the pride of.
  • 38:24So we need to solve this problem.
  • 38:26And with early identification
  • 38:28leading to effective early treatment,
  • 38:31we can change lifetime outcomes.
  • 38:33So the good news also is that
  • 38:35this was the size of, you know,
  • 38:38is half a fridge okay.
  • 38:40This was not something that could
  • 38:42be deployed, you know, very broadly.
  • 38:44So this is what it looks now.
  • 38:49Oops. So this is what it looks now.
  • 38:51So we were able to miniaturize that.
  • 38:53So that's now in a tablet version.
  • 38:56So there is a built in eye tracker and
  • 39:00that tablet can be deployed anywhere
  • 39:03there is Internet connectivity because
  • 39:06the technician can sit anywhere and
  • 39:08that can actually be shipped by a UPS.
  • 39:11So very happy with the way
  • 39:13that things are going.
  • 39:14Now we're very interested in,
  • 39:17in in tailoring those
  • 39:18devices to context of use.
  • 39:20So for those of you who sort of you
  • 39:23know like boring stuff like positive
  • 39:25predictive value and negative
  • 39:27predictive value and Needless to say,
  • 39:29the moment that you sort of
  • 39:31maximize negative predictive value,
  • 39:33you sort of minimize positive
  • 39:35predictive value and vice versa.
  • 39:37And this is basically where our device is,
  • 39:39is right here.
  • 39:41So for the context of a
  • 39:44clinical context of use,
  • 39:46just like the clinical trial that we did,
  • 39:48these are all specialized clinics.
  • 39:50For that then we have that, OK,
  • 39:53sensitivity and specificity are both
  • 39:56optimized and what the results is
  • 39:58that we can actually make statements,
  • 40:01very precise statements of
  • 40:03probabilistic statements of a child
  • 40:06having autism or not having autism,
  • 40:08OK.
  • 40:10One thing that was a serendipitous
  • 40:12kind of a thing we didn't expect
  • 40:14that to happen is that in the sample
  • 40:17for the national clinical trial what
  • 40:19we found out is that if you go by
  • 40:22clinician reference standard diagnosis,
  • 40:24we found that they were both ethnic
  • 40:27and racial bias as you can see here
  • 40:32when we went by the by the device.
  • 40:35Diagnostic classifier.
  • 40:36Both that racial and and and
  • 40:40and ethnicity bias disappeared.
  • 40:43We don't know what that is due to,
  • 40:45but this is something that we
  • 40:48certainly are going to to to focus on.
  • 40:50But let me say something about the
  • 40:52possibility of using this device in the
  • 40:54context of population based screening.
  • 40:56There pediatricians tell us all
  • 40:58the time they don't want to tell a
  • 41:00family that your child has autism,
  • 41:02they want to tell a family your
  • 41:03child does not have autism.
  • 41:05They that's what they want to say and so
  • 41:07you maximize negative predictive value.
  • 41:10So where we to use this device in the
  • 41:13context of population based screening,
  • 41:15we might be able to make those kinds
  • 41:18of of of of statements of probability
  • 41:20including to be able to get to not
  • 41:23over 99% of probability reassuring
  • 41:26the pediatrician you can say to the
  • 41:28family your child does not have autism
  • 41:30basically come out of the system.
  • 41:32Let's focus on those who need our attention.
  • 41:35OK,
  • 41:36very quickly now we we have an NIH
  • 41:39grant now that basically downwards
  • 41:43extends the utilization of this device.
  • 41:47We are pairing with our college pediatricians
  • 41:51pediatric practices at nine month old,
  • 41:54nine month well well baby checkups.
  • 41:57And so the baby goes and finishes
  • 41:59the nine month well baby check
  • 42:00up and then steps into our van
  • 42:02and completes this procedure.
  • 42:04We are now using it truly as
  • 42:08a quantitative population
  • 42:10based screening device.
  • 42:14I want to say one final thing
  • 42:16about something that I've
  • 42:17learned here which is you know,
  • 42:19Sally Province is to say.
  • 42:21Go and spend one year in that daycare,
  • 42:25the hospital daycare,
  • 42:27sit in the corner and do nothing.
  • 42:31Observe, right.
  • 42:33So this is what we've been doing.
  • 42:35This is McDonald and Jim and and
  • 42:39and all of you have taught me is.
  • 42:43You want to be a walking
  • 42:45laboratory of social engagement.
  • 42:47You want to be somebody who
  • 42:48can actually sense how much
  • 42:50children are getting from this.
  • 42:52But can we quantify,
  • 42:53Donald is the one who said,
  • 42:54I mean, this whole business of,
  • 42:56you know, you're a good clinician,
  • 42:57but can you elevate it to
  • 42:59the plane of science?
  • 43:01And Donald is the one who's sort of
  • 43:03prompting us to do this kind of thing.
  • 43:05So here is what life is like, K.
  • 43:09Now this is what typically
  • 43:12developing toddlers are looking at.
  • 43:14This is what a child devotism is looking at.
  • 43:18Let's look now at pointing,
  • 43:19social monitoring,
  • 43:20joint detention being so important.
  • 43:22OK, so this is what the typically
  • 43:24developing children are looking at.
  • 43:26And this is what one single
  • 43:28child devotism is looking at.
  • 43:29And here is now facial affect and
  • 43:32you see where most children are
  • 43:34looking at and you see what the
  • 43:36child devotism is looking at.
  • 43:38And here is another one facial effect.
  • 43:42Can you see and this is where
  • 43:44the child devotism is looking at
  • 43:46and now we can basically there
  • 43:48are hundreds and hundreds of
  • 43:50those examples in our videos.
  • 43:52And So what we're trying to do now is
  • 43:55to derive indices that are skill based,
  • 43:58something that we can actually
  • 44:00give to the interventions and say,
  • 44:03well this is where the child is.
  • 44:05In terms of processing social affect
  • 44:08or facial gestures or or or or or
  • 44:11joint attention or or anything of that.
  • 44:14So one of the things that we're
  • 44:16trying to do now is to derive this
  • 44:19quantitative indices of skill based
  • 44:21milestones for treatment because I
  • 44:23mean you guys know that one of the
  • 44:26things that people who work if a BA
  • 44:28and what not in early intervention.
  • 44:31And treatment is that they spend
  • 44:33a lot of time collecting a lot
  • 44:35of data that is not standardized
  • 44:37that drives payers crazy and takes
  • 44:40hours upon hours upon hours.
  • 44:42And so they need to document
  • 44:43progress or not of the child.
  • 44:45This is time that they are
  • 44:47not providing services.
  • 44:48So that's what we're trying to do as well.
  • 44:50We are trying to basically advise
  • 44:54develop those quantitative
  • 44:55indices of those important skills.
  • 45:00You know, what I've learned in the past
  • 45:0320-30 years in fact working in this
  • 45:07field is that autism is not a disease.
  • 45:10Autism is not a disease.
  • 45:11Autism is a trait.
  • 45:12Autism is a genetic trait.
  • 45:15Autism is something that may
  • 45:16or may not lead to disability.
  • 45:18And whether it does so depends
  • 45:22very much on us if we want to know
  • 45:25where those 95,000 babies that are
  • 45:27born every year who have autism.
  • 45:30Where are they going to end up?
  • 45:32One of the largest treatment programs
  • 45:34that we have at our center is treatment
  • 45:36for severe behavior challenges.
  • 45:38Is a self injury, is a lovement, is.
  • 45:40Is, Is aggression is,
  • 45:42I mean you name it,
  • 45:43K We would like to put that program out
  • 45:47of business because what I've learned
  • 45:49is that the greatest burdens of autism,
  • 45:51the intellectual disability,
  • 45:53the languages ability,
  • 45:54and the severe behavior challenges are not
  • 45:56part of the definition of this condition.
  • 45:58They are not inevitable.
  • 46:00They are the results,
  • 46:03particularly for some children
  • 46:04whose access to any supports come
  • 46:07only during their school years.
  • 46:09So that's what we want and ultimately
  • 46:12we would like to change the narrative
  • 46:14of this condition from one of disability
  • 46:17to one of possibility and promise.
  • 46:21These are all the different foundations
  • 46:23that have been supporting over the years,
  • 46:25the wonderful people who have been
  • 46:28working in all those projects.
  • 46:30Doctor Martin,
  • 46:42I assume that if people would like to
  • 46:45ask questions, I'm here. If we have you
  • 46:47assume correctly and if you are
  • 46:49on Zoom, please let us know.
  • 46:50And if you're in the crowd,
  • 46:52hold on a second.
  • 46:54Doctor Crowley is got it started.
  • 47:02Doctor Clan brings back memories
  • 47:05and it was a great pleasure to see
  • 47:07you head out of the park again.
  • 47:10So I'm going to save some of
  • 47:12my questions for later today.
  • 47:14But my specific question
  • 47:15is the Ados is a gold
  • 47:17standard for assessment of autism and
  • 47:20you're presenting these assessments to
  • 47:23predict to that and I think you said.
  • 47:2568% of the variance was accounted
  • 47:27for and was that right and what
  • 47:28I was thinking little over
  • 47:29that, little over that,
  • 47:30what was it again, what was the
  • 47:33747474? But what I was
  • 47:34thinking was what if the autism
  • 47:36diagnosis is actually or that that
  • 47:39measure is actually imperfect and
  • 47:41your measure actually accounts
  • 47:43for variability in impairment and
  • 47:45functioning and long term things And
  • 47:46do you have any data to speak to that?
  • 47:48So Michael, I will have you speak of the FDA.
  • 47:52Whenever you are developing any
  • 47:55medical device, any medical procedure,
  • 47:57but certainly a medical device procedure,
  • 48:00you need to emulate a reference standard.
  • 48:03You cannot be better than your reference
  • 48:06standard because you're going to be wrong.
  • 48:08You understand what I mean?
  • 48:10So for A, it doesn't matter if
  • 48:12you're working in oncology or or
  • 48:15in diabetes or in in cardiology,
  • 48:17if you are trying to develop a new procedure,
  • 48:20you need to match the reference standard and
  • 48:23in this case the AIDOS is gold standard.
  • 48:26One thing that we never,
  • 48:27we never discusses the fact that the
  • 48:30AIDOS was never approved by the FDA.
  • 48:31You understand that the sensitivity
  • 48:33and specificity of the AIDOS.
  • 48:35Was actually calculated by by
  • 48:38basically looking at the concordance
  • 48:40between the clinician's diagnosis
  • 48:42and the ADAS when the clinician used
  • 48:45the ADAS to make the diagnosis.
  • 48:47So I know it's a that's one thing
  • 48:49that's that you need to consider.
  • 48:50And the second thing is that the ADAS
  • 48:54is not perfect and so there is error
  • 48:57measurement actually that it's quite,
  • 48:59it's quite a bit and yet FDA
  • 49:02disregards this entirely.
  • 49:04ADOS is the gold standard.
  • 49:06You better get close to it.
  • 49:08The the funny part and Kasha would be
  • 49:11able to speak that to that more eloquently
  • 49:13than I in our national clinical trial.
  • 49:17You understand that 29.5%
  • 49:21of all of our sample.
  • 49:23Remember this was a very complicated sample.
  • 49:26These are not kids with without diagnosis.
  • 49:29They have autism or non autistic
  • 49:31developmental delays of all kinds.
  • 49:3329.5% of the cases.
  • 49:34The clinicians from UCSF,
  • 49:36from Seattle Children's,
  • 49:37Cincinnati Children's, Rush,
  • 49:39Emory and and and and and Phoenix had
  • 49:43suboptimal confidence in their diagnosis.
  • 49:46These are 16 to 30 month oldest.
  • 49:48FDA says OK, no,
  • 49:51it should be 100% you should.
  • 49:53You basically they assume the truth,
  • 49:56but the ground truth in our field.
  • 49:58I mean this is a behaviorally
  • 50:00defined condition, so you have to.
  • 50:02Deal with those imperfections.
  • 50:03But absolutely I my heart is
  • 50:06goes of your statements,
  • 50:07but if you want to get it cleared by FDA,
  • 50:11they wouldn't listen to what you just said.
  • 50:17Adam.
  • 50:20Hey Yami, that
  • 50:20was amazing as always.
  • 50:24A lot of questions,
  • 50:24but I'll stick with one,
  • 50:25like very concrete.
  • 50:27Can you talk a little bit about the
  • 50:30curation process for the videos,
  • 50:32for the standardized test,
  • 50:34the video stimuli? Yeah, But how
  • 50:37you selected which ones and
  • 50:38what you were looking for?
  • 50:40Well, we had several generations of videos.
  • 50:45I remembered that,
  • 50:46sort of the one that we used in
  • 50:49all of our experimental studies.
  • 50:51The behavior, genetic studies,
  • 50:53the early developments,
  • 50:55they they were either caregivers and
  • 50:57we remember sort of a lot of actresses
  • 51:00coming to the child study center
  • 51:02sometimes from Calvin Hill that you
  • 51:04come here and they record our videos.
  • 51:06The toddlers came from a preschool actually
  • 51:12an after school program at Guilford Guilford,
  • 51:14Guilford Green.
  • 51:16You probably remember that family as well.
  • 51:19They came from that,
  • 51:21but subsequently we became to enrich
  • 51:23those particularly in terms of Guilford
  • 51:26is not very diverse and so we needed
  • 51:28a little more of diversity in our
  • 51:30videos and things of that nature.
  • 51:31But the funny part and if this is what
  • 51:34you're driving at is that we have a very,
  • 51:37very large program in our center focus
  • 51:40entirely on the Latino population,
  • 51:42particularly non non-english
  • 51:44speaking children and families.
  • 51:47And we also have large grants focused
  • 51:49entirely on African Americans.
  • 51:51I remember Atlanta is 40%,
  • 51:52forty, 7% African American.
  • 51:55So we we have the only NIH genetic
  • 51:59grant genetics grants focused
  • 52:01entirely on African Americans.
  • 52:03And what we're finding out is that,
  • 52:05number one,
  • 52:06those essays are not biased by
  • 52:09either language or race, ethnicity.
  • 52:12And I think the idea is that
  • 52:14probably we're tapping into assays.
  • 52:17That the language that in the
  • 52:18stimuli are not very important,
  • 52:20that are things that are
  • 52:22a little more universal,
  • 52:23but that's absolutely something
  • 52:24that we're going to be working on.
  • 52:26Were there also like certain
  • 52:28kinds of sorry, were there also like
  • 52:32specific kinds of social interactions
  • 52:33that you're hoping to capture?
  • 52:37To be truthful, no.
  • 52:40We started by basically filming children.
  • 52:43Well, we have caregivers.
  • 52:45Directed infant directed speech,
  • 52:46we have a whole program of
  • 52:48research focused on live.
  • 52:50Live tracking for example
  • 52:52is bidirectional tracking is
  • 52:55caregiver infant interaction live.
  • 52:58And so that's live of course,
  • 53:00but in terms of the videotapes that we use.
  • 53:03They were basically trying to get as
  • 53:07varied as varied as sampling of of
  • 53:11toddler interactions as we could.
  • 53:13It has to be developmentally
  • 53:15appropriate of course.
  • 53:15But what I remember one thing
  • 53:18that I think Kyle once said we
  • 53:20were sort of being trained on the
  • 53:22on the Gazelle schedules and it
  • 53:23was like gosh this looks so much,
  • 53:25you know that how interactive the
  • 53:27psychologist he looks so much like
  • 53:29this test and that test and I think
  • 53:31you said something the effect.
  • 53:32Yeah, come on.
  • 53:33Toddlers don't do that much right?
  • 53:36So you're going to have a lot
  • 53:37of commonalities.
  • 53:38We try to grab as much as possible with that.
  • 53:41Doctor Pruitt thinks
  • 53:42toddlers do as much or more
  • 53:47toddlers. They're the best.
  • 53:48It's the last time.
  • 53:49The mind and body are good friends.
  • 53:52That's why we love them so much.
  • 53:55After that, the mind takes over
  • 53:56and it's downhill forever.
  • 53:59And we cannot free ourselves from our
  • 54:01mind the rest of our lives. Kyle,
  • 54:03I ami you.
  • 54:07I've been I've been wondering
  • 54:08for years how we let you go.
  • 54:10Now I realize why you had to,
  • 54:12so that you could do this.
  • 54:13And this is such an amazing gift
  • 54:16to clinicians particularly.
  • 54:19The burden that you lift from
  • 54:21Pediatrics to say so many parents
  • 54:23worried about their children,
  • 54:24there's something off.
  • 54:25What is it? Are they autistic?
  • 54:27To be able to say no liberates
  • 54:29both the physician and the family
  • 54:31and lets them get on their path
  • 54:33so the pediatrician can pay
  • 54:34attention to the ones that need.
  • 54:35It's it's an amazing gift.
  • 54:37I'm struck by one of the small little
  • 54:40quotes in your side that said you
  • 54:42know that these these children create
  • 54:45their own experience and to the parents.
  • 54:48They're not part of it and that's
  • 54:51a very bitter pill to swallow,
  • 54:53to treat it as a trait and to
  • 54:55say we can help you with that,
  • 54:57let's get started and let's get started
  • 55:00together is such an immensely repairing,
  • 55:03phenomenal interpersonal experience
  • 55:05between the clinician and a parent,
  • 55:08as opposed to waiting for 3-4 five years.
  • 55:12The kid you know explodes
  • 55:14kindergarten and say, wow,
  • 55:15there's something really
  • 55:16wrong with this child.
  • 55:18To have eliminated,
  • 55:19you know,
  • 55:20hundreds of thousands of negative
  • 55:23experiences from ever happening with
  • 55:26your wonderful toy is quite a gift.
  • 55:29And it's not just exciting,
  • 55:32it's a real game changer.
  • 55:33And I'm thinking of the institutions
  • 55:35that need to know about this
  • 55:37yesterday so that it can wind up in
  • 55:39the hands of people in the country,
  • 55:42and I mean in the country.
  • 55:44Wi-Fi access remains in the issue.
  • 55:47They'll have to get busy with
  • 55:49their legislators to get it.
  • 55:50But this is worth the this is
  • 55:53worth the candle. And I thank you.
  • 55:56And I remember Sally saying,
  • 55:58we we do not understand autism.
  • 56:00It starts so early.
  • 56:01We are completely at the wrong
  • 56:03end of this dog. We have start.
  • 56:05We have to start working with the head,
  • 56:07not the tail. And you did that.
  • 56:09Thank you.
  • 56:10Kyle.
  • 56:11I must say this. I know I am in New Haven.
  • 56:14I know that I yell when I receive an e-mail.
  • 56:17From a former patient
  • 56:19whom I saw for 15 years,
  • 56:21every Tuesday that person was first seen.
  • 56:25He's my age. He was served.
  • 56:27First seen at the Health Child Study Center
  • 56:30at the age of 20 months by Sally and by Sam.
  • 56:35And then Donald was involved.
  • 56:37I assume Jim must have involved.
  • 56:39I don't know if Bob was involved.
  • 56:41Eventually he ended up with me.
  • 56:44And he wrote to me the most heart warming.
  • 56:49I I'm talking about Tom and
  • 56:53what a distinguished family.
  • 56:55Yale family. But my goodness me.
  • 56:57But what I'm saying here is this.
  • 57:00This is just a toy.
  • 57:02The concepts.
  • 57:04The concepts came from you.
  • 57:06It came from Linda, it came from Jim,
  • 57:08it came from Donald, it came from Fred.
  • 57:10And I mean this center to me is
  • 57:14really a monument to the impact
  • 57:18of relationships in one's life.
  • 57:21When, when, when, when?
  • 57:23My my good friend Dr.
  • 57:25Martin was editing that book.
  • 57:27That book, Donald's book,
  • 57:29was all about relationships,
  • 57:31life being a correct collection thereof,
  • 57:34to my mind, Brain is.
  • 57:36Exactly.
  • 57:36That is the instantiation
  • 57:38of those experiences.
  • 57:39But let me speak just very briefly
  • 57:41substantively to one thing that you said,
  • 57:44yes, they are creating that
  • 57:46experience and their parents,
  • 57:47their children were born with an
  • 57:49attenuated sense of the other.
  • 57:51So the parents are not what
  • 57:53they are cocreating.
  • 57:54Having said that,
  • 57:56we can engineer that environment to
  • 57:58empower families so that we can strengthen
  • 58:01them mutuality that that that sense of of.
  • 58:06Typical connection and and
  • 58:08and and and engagement.
  • 58:10But here is what we found out because
  • 58:13you work with that population,
  • 58:15you know with teen moms and very,
  • 58:18very,
  • 58:19very,
  • 58:19very low income mothers were
  • 58:22extraordinarily fragile.
  • 58:23They leaving situations of stress and
  • 58:25gales when you are telling them that's
  • 58:28something that they can't actually do,
  • 58:30meaning they can engage that baby.
  • 58:33And that engagement will promote
  • 58:36optimal development in that child.
  • 58:39The sense of empowerment
  • 58:41that one conveys is huge.
  • 58:43So nothing that I said today is new
  • 58:47because it came from all of you.
  • 58:49Thank you.
  • 58:50Is that the final word?
  • 58:51That's such a beautiful final word,
  • 58:53but there may be a final, final word.
  • 58:54There's two questions.
  • 58:56There's more questions that I think we're,
  • 58:58I think we're going to be
  • 59:00respectful of your time and ever.
  • 59:01And I mean you know your your
  • 59:03love note to to the center.
  • 59:05We feel it and we send it back and
  • 59:07come back again and again and again.
  • 59:09Thank you.
  • 59:10Thank you very much.