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We know that genes are building the brains of these babies differently,

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and we're asking the question, well, can we detect those brain differences

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much earlier than we see the behavioral symptoms themselves?

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The human brain is the most complex structure in the known universe,

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and we are in the middle of a scientific revolution to understand its inner workings.

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Join us for a conversation with world-renowned neuroscientists

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as they visit Rochester.

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I am Dr. John Foxe, Director of the Del Monte Institute for Neuroscience

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at the University of Rochester, and you are listening to Neuroscience Perspectives.

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So, Helen Tager-Flussberg from Boston University,

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it's really a great honor for me to have this conversation with you.

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It's a pleasure to be here, John. Thank you for inviting me.

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Absolutely. I think we're going to spend some time talking about autism,

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but I also, you know, we want to talk about you.

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So, let's start out there. How did you end up being

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one of the top autism researchers in the country?

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That's my opinion.

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Well, thank you, John. I have no idea.

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I think I was in the right place at the right time.

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I started out long before anyone had ever heard of autism.

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This was over 40 years ago.

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I was always interested in language development,

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and I was looking for a population where I could study language development,

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and I picked autism.

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Nobody in the group, nobody had studied it really very much,

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and I thought this would be a wonderful place to start.

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But why language development? How did you get to that?

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Why I was interested in language,

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because language is the most intrinsically interesting, deep,

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and essentially human domain of functioning.

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Through language, we can understand everything about an individual.

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And language development itself is just such an amazing, remarkable process.

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And I just always found it extremely interesting and exciting.

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So, that's really what motivated me, was to study,

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was to understand the process of language development,

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how a child goes from the age of 12 months,

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where they may or may not have one or two words,

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to being a three-year-old 24 months later,

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speaking in full and complex and rich sentences,

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coming up with ideas and stories out of nowhere.

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And they do it effortlessly.

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And then, there's the whole group of children who don't get there.

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And I thought, at that time, I was in an experimental psychology program.

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I'm not a clinician by training.

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But my interest was driven in part by the idea that if we studied children

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for whom acquiring language was not straightforward,

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and who didn't end up in the same place,

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that would give us insight into what some of the mechanisms are

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that drive language development.

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This was a time when we couldn't look inside the brain,

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where we couldn't look inside the human genome.

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We couldn't use biology to help drive any of our work.

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We just were relying on behavior.

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And so, the behavior of disordered populations would provide insight.

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But then, you immediately get caught up in the problem itself.

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And from there on, my career took off.

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Can we rewind the tape?

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Because people watching in will immediately realize

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that you didn't grow up in this country.

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So take us back to London and how you transitioned from London to...

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Right. So I did.

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I grew up in...

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And I was born and raised in London.

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And I was an undergraduate.

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I got my undergraduate degree at University College London.

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And when I was growing up, I mean, I have a younger sister

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who has intellectual disability, who is quite verbal,

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but whose language never reached the point of full maturity.

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So I don't know that...

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So a very personal connection to the...

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Yeah. I don't know that that was...

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I mean, I think that's what drove me to being interested in psychology in general.

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I had been planning.

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I had been planning to study mathematics at university.

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But I also recognized that I probably couldn't make that next step in mathematics.

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And I found when I discovered the field of psychology, I thought,

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well, this is a science that I think would be very interesting to me.

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I was also toying with physics, but I was very good at physics,

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but I never felt that I understood the concept.

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So I could do it, but I felt like I didn't understand it.

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And I had the naive view that maybe, well, people I could understand,

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not realizing that, of course, people are infinitely more complex

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than physics particles are.

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Anyway, so that's how I started.

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But then...

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And then the jump from Britain to the US, how did that come about?

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I wanted to pursue a PhD, and I couldn't see myself continuing in England.

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At that time, mid-70s, things were very depressed there.

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I looked around at the graduate students at University College London.

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They all seemed extremely morose and unhappy.

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The undergraduates all were having the time of their lives,

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and the graduate students seemed miserable.

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And then I came and visited the United States,

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and everybody here seemed like they were very purposeful and excited,

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and seemed to enjoy their lives as graduate students.

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And I always had a love of America.

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I think all along, part of me knew I would jump ship.

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I would cross the Atlantic and never go back, and that's what happened.

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So now, you come to the US at that point where you were beginning to think about

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intellectual disabilities and language delay as part of the PhD, or when did that come?

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No, I was pursuing studies of language development in typically developing children.

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And then when it came time to pick my dissertation topic,

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I was in a...

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My mentor was Roger Brown, who was the father of developmental psycholinguistics.

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And he encouraged...

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He himself was fascinated by language in all different populations,

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schizophrenia, aphasia, Down syndrome, foreign language acquisition,

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which is really interesting and important, the role of parent input.

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So he encouraged each of his students to sort of pick off a tool,

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a topic that they would sort of make their own.

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So I worked collaboratively with other students on studies of language development.

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But then when it came time to pick off my own topic, I turned to autism,

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not realizing that that was an extremely rash decision, because at that time,

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the incidence was around four in 10,000.

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So what was... And I was not a clinician.

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And so that was very presumptive of me to think that I could go out there and do this.

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Find all of those kids and...

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Yeah, well, I traveled a lot to do so.

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And that I could do this without being a clinical psychologist,

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because in England, you could do that.

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People didn't care what your credentials were.

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If you had interesting scientific questions, you could pursue them.

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And there was a group in England who had started to do that.

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And I had been fortunate enough and heard lectures from them directly.

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So I thought I could do that here.

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And then I discovered that's not quite so simple, but I persevered.

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Well, let's go back to that incidence business, right?

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Because four in 10,000, one in 2,500 kids, when you started out,

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that was what people believed that was the prevalence of autism.

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Today, it's one in 40.

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There are thereabouts.

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40, 50, 60, whatever number you would...

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So what happened?

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What happened to cause that increase?

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I think a lot of things, some of which we have some good evidence for,

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and others for which we don't.

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We know that there were changes in the diagnostic criteria,

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and our whole conception of what autism is,

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which now has more to do with the presence of particular traits,

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perhaps the low end of the normal distribution of particular traits.

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But we also have a lot of diagnostic substitution.

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So as the rates of autism have risen,

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the rates of individuals whose primary diagnosis is intellectual disability

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has declined precipitously.

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So recategorization of children who would formally have been diagnosed

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with an intellectual disability, and now they're being put in the autism pot.

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And there's two things going on there, I think.

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One of it is that indeed they do have autism, and they did have autism all along,

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but it wasn't recognized because once you see the intellectual disability,

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you put one label on and you stop there.

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And people were not very knowledgeable, and we didn't have many experts

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who could diagnose autism.

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So one of it is that they were probably previously misdiagnosed.

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And understanding what the relationship is between autism

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and intellectual disability has always had a sort of murky history.

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And I think the second thing is, if you have intellectual disability,

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the same kinds of therapeutic interventions, for example,

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applied behavioral analysis in any or every one of its forms,

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is an extremely useful and important form of intervention.

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In fact, it started out being an intervention for children with intellectual disability,

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and then switched to autism.

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Nowadays, you can't get ABA services if you don't have a diagnosis of autism.

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And so therefore, it becomes very important to provide children who you know

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are going to benefit from these therapies with the diagnosis that's going to

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provide them access to those therapies.

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So that's just one piece of the picture.

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I think it's way more complicated than that.

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Sure. Now, one of the things I know about you that our viewers may not know

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is that you're really famous in the field for being really a pioneer.

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You're the person who went where everybody else feared to thread.

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And that is that many of us who work in the autism field,

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we are inclined to work with what we call high-functioning children with autism.

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And we do it most likely really because they're much easier to work with.

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But of course, they're not nearly as afflicted.

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And you right from the get-go jumped right in.

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Well, maybe not so.

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No, that's really not true.

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But you have gone down and worked with the kids who really have severe autism.

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That's really only been the last eight to ten years, John.

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I really didn't.

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I said to myself, well, I'm interested in language.

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You can't study language in an individual who doesn't have, who doesn't speak.

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So therefore, I only focused on children who had at least some spontaneous spoken language.

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But time went on and my career flourished.

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And we learned lots and lots of things along the way about language and social cognition

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and many other aspects of children and adolescents with autism.

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But at the back of my mind, I thought, but there are all those kids who don't speak.

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And we're ignoring them.

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And they need us most.

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And they do need us most.

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But until I, I mean, really, I think it took me a long time to open my eyes to that.

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And at the same time, opportunities came about because it is, as you say, and as you know,

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because you have also been involved in work in this area, it is extremely challenging.

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And it costs approximately, I would say, four times as much to do this research as it does

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with the more verbal individuals with autism.

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It really does take a huge amount of resources to do this work.

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And so I was helped along the way.

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I received a pilot grant from Autism Speaks, which had become interested in this population.

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Actually, it was Portia Iverson from CAN, who insisted that Autism Speaks continue this

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initiative that she had begun before they merged with Autism Speaks.

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And so I got some pilot funding to investigate using eye tracking methods as an approach

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to exploring language comprehension in minimally verbal children.

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And so that was quite interesting.

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And then the NIH became interested as well.

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And I had already had a leg up with this.

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And I co-directed a workshop that looked into sort of who are these kids and what could

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we be doing for the NIH.

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I did that with Connie Casery from UCLA.

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And I think that really set the ball rolling for me.

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And I think I became fully committed to the idea that this is a very important project

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because this is where we need to be doing research.

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And coincidentally, I think at the same time as I was doing that work, we had people within

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the autism community itself who were beginning to push back against the kind of work that

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many of us had been doing, you know, perhaps exploring language processing, exploring theory

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of mind impairments, whatever else we were doing saying this isn't useful to us.

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These are people within the autism community.

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That kind of work isn't useful to us.

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Why aren't you doing the research, which is important to me personally, you know, and

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to the rest of my community?

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And so it's sort of interesting.

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I sort of stopped doing that work at a time when, you know, there were also other forces

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saying maybe this isn't the most important work we could be doing.

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Well, can you unpack that for us?

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What is the community crying out for?

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What do they want from the research community?

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It started out, I think, with an interest, even, you know, sort of quite independent,

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very verbal, intellectually able people living on their own.

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Nevertheless, for them, language isn't a problem.

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That they have difficulty with social relationships, yes, okay.

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But hey, don't we all, right?

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Depending on how you define that.

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For them, some of the sensory issues were more, so if we're going to take a sort of

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more scientifically based research topic, people were not investigating the sensory

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issues as much.

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I think the exception is the group here at the University of Rochester under Dr.

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Louisa Bonetto.

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She's had a long standing interest, but she was really way ahead of the curve at this.

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So I think there was that.

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But I would say since then, the cry from the autism community itself about what kind of

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research is more in the area of services and supports and less in the area of scientific

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research.

242
00:18:10,800 --> 00:18:11,440
Right, right.

243
00:18:12,640 --> 00:18:18,720
So, you know, I think we're getting a sort of more complex message about scientific

244
00:18:18,720 --> 00:18:23,520
research on autism that comes from the autism community.

245
00:18:24,480 --> 00:18:31,600
Which is not to say that the needs for understanding a better way for delivering

246
00:18:31,600 --> 00:18:36,880
services for that's these are really, really important.

247
00:18:36,880 --> 00:18:37,360
Yeah.

248
00:18:38,320 --> 00:18:43,200
The brass tacks of the day to day life of living with a child with autism.

249
00:18:43,200 --> 00:18:45,840
You're worried about getting your kid to the doctor.

250
00:18:45,840 --> 00:18:47,600
You're worried about GI issues.

251
00:18:47,600 --> 00:18:52,640
And of course, for our community, we are saying we really need to understand the basic

252
00:18:52,640 --> 00:18:56,880
neurobiology forever to really get to meaningful interventions.

253
00:18:56,880 --> 00:19:00,320
But that's it's the long term piece of that.

254
00:19:00,320 --> 00:19:04,480
That's further down the road and it's not what people are dealing with day in, day out

255
00:19:04,480 --> 00:19:05,280
struggling with.

256
00:19:05,280 --> 00:19:05,600
Right.

257
00:19:05,600 --> 00:19:11,440
I will say that the work we're doing with minimally verbal children and adolescents,

258
00:19:11,440 --> 00:19:15,200
I think that does resonate very well with the families.

259
00:19:15,200 --> 00:19:24,960
They understand that we do need to understand why these children don't learn to speak.

260
00:19:25,600 --> 00:19:27,600
I think for them, this is important.

261
00:19:27,600 --> 00:19:33,520
I think it's even more important that we develop effective interventions, effective

262
00:19:33,520 --> 00:19:37,680
approaches to providing them with a means for communication.

263
00:19:37,680 --> 00:19:39,360
That's absolutely crucial.

264
00:19:39,360 --> 00:19:45,280
And I don't think the community of researchers, whether they're clinical or basic

265
00:19:45,280 --> 00:19:48,720
biologists have yet stepped up to that responsibility.

266
00:19:48,720 --> 00:19:55,120
You know, I think for me, I need to know why they don't speak and then can think about

267
00:19:55,120 --> 00:19:56,720
targeted interventions.

268
00:19:56,720 --> 00:20:01,920
But my colleague, Connie Casra at UCLA has already forged the way there.

269
00:20:01,920 --> 00:20:06,160
In terms of actually providing interventions.

270
00:20:06,160 --> 00:20:16,880
Yes, a combination we know of highly targeted intervention that trains social

271
00:20:16,880 --> 00:20:22,240
communication, joint attention, builds up the play skills, the motivation really to

272
00:20:22,240 --> 00:20:31,360
communicate, which these kids need, coupled with an augmentative communication device,

273
00:20:31,360 --> 00:20:39,600
usually now an iPad, it used to be on the Dynavox, actually is very helpful to get

274
00:20:39,600 --> 00:20:41,600
these children to communicate more.

275
00:20:41,600 --> 00:20:43,600
So that's one thing.

276
00:20:43,600 --> 00:20:46,720
There's probably way more that we could be doing.

277
00:20:46,720 --> 00:20:52,880
And I'm hoping over the next several years to be exploring some of that.

278
00:20:52,880 --> 00:20:54,880
Let's talk about biomarkers.

279
00:20:54,880 --> 00:21:00,240
So we've been talking about, so also in your lab, you use electrophysiology and imaging

280
00:21:00,240 --> 00:21:03,040
techniques to measure actual brain function.

281
00:21:03,040 --> 00:21:07,040
Talk a bit about why that's important, where it's leading us.

282
00:21:07,040 --> 00:21:11,040
So biomarkers is a very general term.

283
00:21:11,040 --> 00:21:13,840
And there are different types of biomarkers.

284
00:21:13,840 --> 00:21:20,560
And there are different types of biomarkers that we could be looking for in the field

285
00:21:20,560 --> 00:21:22,560
of autism.

286
00:21:22,560 --> 00:21:26,560
We've been particularly focused on diagnostic biomarkers.

287
00:21:26,560 --> 00:21:36,080
So can we, instead of diagnosing autism on the basis of overt behavioral symptoms,

288
00:21:36,080 --> 00:21:43,600
which we know based on now a decade or more's worth of research by multiple groups of

289
00:21:43,600 --> 00:21:48,000
investigators, it emerges, they emerge during the second year of life.

290
00:21:48,000 --> 00:21:51,680
The exact timing may vary from one child to another.

291
00:21:51,680 --> 00:21:57,200
The exact symptoms that emerge first over time may vary from one child to another.

292
00:21:58,400 --> 00:22:04,640
There are subtle behavioral signs earlier that are a little less specific and a little

293
00:22:04,640 --> 00:22:05,840
less predictive.

294
00:22:05,840 --> 00:22:14,880
But nevertheless, we see retrospectively, certainly are related to the emergence, the

295
00:22:14,880 --> 00:22:16,880
slow emergence behaviorally.

296
00:22:18,560 --> 00:22:20,160
But what about the brain?

297
00:22:22,080 --> 00:22:25,760
We know that this is a highly heritable disorder.

298
00:22:27,200 --> 00:22:33,040
We also know that it's genetically based even when it's not heritable.

299
00:22:33,040 --> 00:22:40,000
We study the heritable version in that we take babies who have an older sibling with

300
00:22:40,000 --> 00:22:40,720
a disorder.

301
00:22:40,720 --> 00:22:46,160
And we know now that about one in five of those babies are going to end up with an

302
00:22:46,160 --> 00:22:47,440
autism diagnosis.

303
00:22:48,080 --> 00:22:53,680
And the question that we're asking in our work, and this is a collaboration between

304
00:22:53,680 --> 00:23:00,080
Boston University and Boston Children's Hospital, my main collaborator is Charles Nelson,

305
00:23:00,080 --> 00:23:03,360
who's a world renowned developmental neuroscientist.

306
00:23:03,360 --> 00:23:04,000
Very much so.

307
00:23:05,440 --> 00:23:13,360
And really, he's the driving force behind all the biology work I learn every day from

308
00:23:13,360 --> 00:23:19,600
him and our other collaborators who bring even more sophisticated approaches to analyzing

309
00:23:19,600 --> 00:23:20,240
our data.

310
00:23:21,120 --> 00:23:25,760
We know that genes are building the brains of these babies differently.

311
00:23:25,760 --> 00:23:32,000
And we're asking the question, well, can we detect those brain differences much earlier

312
00:23:33,040 --> 00:23:36,960
than we see the behavioral symptoms themselves?

313
00:23:36,960 --> 00:23:44,640
And so we've been collecting electrophysiological data, that's sort of electrical recordings

314
00:23:44,640 --> 00:23:46,400
from the surface of the head.

315
00:23:46,400 --> 00:23:48,160
It's completely non-invasive.

316
00:23:49,040 --> 00:23:50,800
The babies don't mind this at all.

317
00:23:50,800 --> 00:23:56,960
And we collect the data at regular intervals over the first few years of life.

318
00:23:56,960 --> 00:24:02,560
And then by the time the babies reach the age of two or three years old, we're able

319
00:24:02,560 --> 00:24:09,040
to confirm whether or not they meet criteria for a diagnosis of autism.

320
00:24:09,520 --> 00:24:19,600
And what we've been finding is that EEG, just resting EEG, in other words, is a very

321
00:24:19,600 --> 00:24:21,040
high-level activity.

322
00:24:21,040 --> 00:24:21,840
So the electrical signals.

323
00:24:21,840 --> 00:24:29,520
The electrical activity that you collect from the brain before you even give the child a

324
00:24:29,520 --> 00:24:38,960
task to do, because we're also doing that, is itself highly predictive of whether this

325
00:24:38,960 --> 00:24:42,240
particular baby is going to end up with autism.

326
00:24:42,240 --> 00:24:42,800
Right.

327
00:24:42,800 --> 00:24:44,080
And give us a timeline.

328
00:24:44,080 --> 00:24:46,960
Are we talking eight months, six months, a year?

329
00:24:46,960 --> 00:24:49,520
Whereabouts are we starting to get that level of prediction?

330
00:24:49,520 --> 00:24:50,560
We collected data.

331
00:24:50,560 --> 00:24:55,600
We collected three, six, nine, 12, plus, plus, plus.

332
00:24:55,600 --> 00:24:56,080
Right.

333
00:24:56,880 --> 00:25:01,920
Well, it's a little murky in our data because we have fewer babies at three months.

334
00:25:01,920 --> 00:25:09,040
We only added on the three-month data point when we were later in the study.

335
00:25:10,800 --> 00:25:14,640
And we have the most robust data at six and nine months.

336
00:25:14,640 --> 00:25:18,880
So six and nine months look like it's the most predictive, but I have a feeling that

337
00:25:18,880 --> 00:25:20,080
it's actually three months.

338
00:25:20,080 --> 00:25:25,680
When we look at the developmental trajectories, we see that there are maximal differences

339
00:25:25,680 --> 00:25:36,400
early on and that over time, the EEG signal becomes closer to what we see in the typical

340
00:25:36,400 --> 00:25:37,840
low-risk babies.

341
00:25:37,840 --> 00:25:38,320
Right.

342
00:25:38,320 --> 00:25:46,800
So there's a sense in which the brain as it is now living in the world and taking in sights

343
00:25:46,800 --> 00:25:54,400
sounds and smells and touch from parents and they are socially engaged and they are engaged

344
00:25:54,400 --> 00:25:59,120
with the world of objects as infants during this first year of life.

345
00:25:59,680 --> 00:26:05,680
Their brains are developing rapidly as are the brains of all babies.

346
00:26:06,240 --> 00:26:14,720
And at some level, they are now the rhythms of the brain that we pick up with EEG become

347
00:26:14,720 --> 00:26:18,720
more similar to the typical babies.

348
00:26:19,280 --> 00:26:23,680
Nevertheless, there are still some differences.

349
00:26:23,680 --> 00:26:30,160
It's harder to use it as a biomarker later, but that's not to say that the brains are

350
00:26:30,160 --> 00:26:31,200
not different.

351
00:26:31,200 --> 00:26:35,040
They're going to be different in different ways at that point.

352
00:26:35,040 --> 00:26:36,160
Go with me on this.

353
00:26:36,160 --> 00:26:42,720
So imagine now, you know, we're a year down the road and your EEG test turns out to be

354
00:26:42,720 --> 00:26:44,160
100% predictive.

355
00:26:44,160 --> 00:26:48,800
You can absolutely say that this child at three months of age is going to go on to pick

356
00:26:48,800 --> 00:26:50,560
up a diagnosis of autism.

357
00:26:50,560 --> 00:26:51,680
What does that do for us?

358
00:26:52,960 --> 00:26:58,640
Well, first of all, I would say step back a minute, John, and don't get so excited.

359
00:26:58,640 --> 00:26:58,960
Okay.

360
00:26:59,680 --> 00:27:05,680
Number one, we've only demonstrated that in infants who have an older sibling.

361
00:27:05,680 --> 00:27:06,880
We have no idea.

362
00:27:07,440 --> 00:27:07,760
All right.

363
00:27:07,760 --> 00:27:13,440
The majority of children who are diagnosed with autism don't come from a family where

364
00:27:13,440 --> 00:27:15,200
there is already an older sibling.

365
00:27:15,200 --> 00:27:21,360
We don't know whether this biomarker is going to extend to the full population of autism.

366
00:27:21,360 --> 00:27:22,160
That's number one.

367
00:27:22,800 --> 00:27:28,400
Number two, we don't know whether it is specific to autism.

368
00:27:30,000 --> 00:27:34,800
Would we see the same difference, the same biomarker?

369
00:27:35,520 --> 00:27:40,560
Would that predict also not to autism, but to ADHD?

370
00:27:40,560 --> 00:27:46,560
Or would it predict to intellectual disability or developmental language disorders?

371
00:27:46,560 --> 00:27:49,680
So we don't know the specificity.

372
00:27:51,360 --> 00:27:52,400
I'm less concerned about-

373
00:27:52,400 --> 00:27:53,120
I'm with you there.

374
00:27:53,120 --> 00:27:57,520
I mean, obviously, I was positing something that was highly unlikely at this point.

375
00:27:57,520 --> 00:27:59,920
So there's absolutely a lot of work to be done.

376
00:27:59,920 --> 00:28:04,000
And really, we're probably looking at a decade or more of work being realistic, right?

377
00:28:04,000 --> 00:28:04,480
Yes.

378
00:28:04,480 --> 00:28:07,440
But again, somebody weighs a magic wand.

379
00:28:07,440 --> 00:28:11,200
If it works, then I'm quite convinced.

380
00:28:11,200 --> 00:28:15,840
First of all, it wouldn't concern me so much if it wasn't specific to autism.

381
00:28:15,840 --> 00:28:16,640
Right.

382
00:28:16,640 --> 00:28:17,040
Okay.

383
00:28:17,600 --> 00:28:28,000
Because I think to detect any neurodevelopmental disorder very early on in life is important.

384
00:28:28,000 --> 00:28:33,040
And it matters more that we're picking up a child, a baby who we know is at risk for

385
00:28:33,040 --> 00:28:37,840
some problem matters more than what specific problem it's going to be.

386
00:28:37,840 --> 00:28:43,760
And we know now that there's way more overlap among all these neurodevelopmental disorders.

387
00:28:43,760 --> 00:28:46,080
They don't fit in neat separate boxes.

388
00:28:46,080 --> 00:28:51,840
So number two is less concerning to me, but I think we'd want to know that.

389
00:28:52,400 --> 00:29:02,160
But I think it fundamentally will change how we approach and how we will think about

390
00:29:02,160 --> 00:29:04,800
autism at a societal level.

391
00:29:05,440 --> 00:29:16,880
And I think we would have to take this quite slowly to prepare parents for the idea that

392
00:29:16,880 --> 00:29:25,680
we can predict something long before, a year or more before the behavioral signs are going

393
00:29:25,680 --> 00:29:26,320
to appear.

394
00:29:27,120 --> 00:29:30,080
That is a whole different landscape.

395
00:29:30,080 --> 00:29:30,560
Right.

396
00:29:30,560 --> 00:29:41,280
And I think we need to think carefully and work with people who are experts in understanding

397
00:29:41,920 --> 00:29:51,280
how all these new directions in medicine can be more comfortably taken up by society

398
00:29:52,400 --> 00:29:54,080
than I'm personally equipped to do.

399
00:29:54,080 --> 00:29:55,680
I'm not experienced with that.

400
00:29:55,680 --> 00:30:00,320
I think about it from the parent perspective, but I also think about it from the clinician's

401
00:30:00,320 --> 00:30:01,360
perspective.

402
00:30:01,360 --> 00:30:03,600
What is this going to mean to pediatricians?

403
00:30:04,800 --> 00:30:08,400
And I've only had informal conversations so far.

404
00:30:09,200 --> 00:30:11,840
Pediatricians would love this.

405
00:30:12,960 --> 00:30:20,400
This takes off their hands a problem that they don't know what to do with in their

406
00:30:20,400 --> 00:30:21,760
everyday practice.

407
00:30:22,400 --> 00:30:29,440
They know that a significant number of babies coming through their well-baby visits are

408
00:30:29,440 --> 00:30:34,480
going to end up with autism or another neurodevelopmental disorder.

409
00:30:34,480 --> 00:30:37,600
And they deal with worried parents all of the time.

410
00:30:37,600 --> 00:30:40,880
And they don't quite know how to fit this all together.

411
00:30:41,680 --> 00:30:47,920
And they spend 15 minutes, that's the time they are allotted by the insurance companies

412
00:30:47,920 --> 00:30:49,600
for their well-baby visits.

413
00:30:51,360 --> 00:30:57,840
And during that time, can that pediatrician pick up that, yes, maybe there's a subtle

414
00:30:57,840 --> 00:31:00,800
difference in the amount of babbling that this baby is doing?

415
00:31:00,800 --> 00:31:02,480
No, they can't do that.

416
00:31:02,480 --> 00:31:03,680
They don't know what to do.

417
00:31:03,680 --> 00:31:05,280
They've got a very worried mom.

418
00:31:05,840 --> 00:31:08,160
They don't quite know what to do with that.

419
00:31:08,160 --> 00:31:16,400
So even though by 18 months they're mandated to do screening, a pediatrician doesn't really

420
00:31:16,400 --> 00:31:24,160
want to say to the mother of an 18-month-old who looks like they've failed the screener,

421
00:31:24,160 --> 00:31:26,160
oh, I think your child may have autism.

422
00:31:26,160 --> 00:31:29,200
I'm going to recommend that you see a specialist.

423
00:31:29,200 --> 00:31:30,960
They usually try to pass it along.

424
00:31:30,960 --> 00:31:32,640
Oh, well, let's wait and see.

425
00:31:32,640 --> 00:31:35,200
When you come back at two, we'll reevaluate.

426
00:31:35,200 --> 00:31:41,520
That's the way pediatricians do it because they don't know how to deal with the evidence.

427
00:31:42,080 --> 00:31:43,840
They don't know what to make of it.

428
00:31:43,840 --> 00:31:44,640
Right, right.

429
00:31:44,640 --> 00:31:48,160
So an objective test would really help them.

430
00:31:48,160 --> 00:31:51,280
For them, they say the idea of a biomarker would be...

431
00:31:51,280 --> 00:31:52,720
EEG, they understand.

432
00:31:53,520 --> 00:31:54,800
So they would love that.

433
00:31:54,800 --> 00:31:58,240
The issue is no test is going to be 100%, John.

434
00:31:58,240 --> 00:31:58,960
Right.

435
00:31:58,960 --> 00:31:59,600
Okay.

436
00:31:59,600 --> 00:32:04,640
We're always dealing with risk markers that are probabilistic.

437
00:32:05,200 --> 00:32:09,040
And so another whole piece of how we're going to cope with this...

438
00:32:09,040 --> 00:32:10,640
And I think this is going to come.

439
00:32:11,280 --> 00:32:15,040
It's going to come five, 10 years from now.

440
00:32:15,040 --> 00:32:19,200
And if it's not our biomarker, it's somebody else's biomarker.

441
00:32:19,200 --> 00:32:21,120
It doesn't matter to me whose it is.

442
00:32:21,120 --> 00:32:25,840
But it will provide us with a way of screening universally.

443
00:32:26,480 --> 00:32:27,760
That would be easily...

444
00:32:27,760 --> 00:32:29,760
I like EEG because it's cheap.

445
00:32:29,760 --> 00:32:31,280
Okay.

446
00:32:31,280 --> 00:32:34,720
It's cheap, it's portable, it's accessible.

447
00:32:34,720 --> 00:32:40,240
This doesn't take very long to do, at least the measures that we have.

448
00:32:40,240 --> 00:32:46,560
So, Helen, going back to your training and your trajectory, you come from London,

449
00:32:46,560 --> 00:32:47,920
you end up at Harvard.

450
00:32:47,920 --> 00:32:53,840
You come from London, you end up at Harvard, and you're one of the only PhD students at Harvard?

451
00:32:53,840 --> 00:32:54,720
That's a woman, is that...

452
00:32:55,360 --> 00:32:57,440
There were some in the experimental program.

453
00:32:57,440 --> 00:32:59,360
It depends which program you were looking at.

454
00:32:59,360 --> 00:33:04,240
I was an experimental and we certainly had the fewest women in our program.

455
00:33:04,240 --> 00:33:08,160
So what was it like to be a woman in the field in those days?

456
00:33:10,240 --> 00:33:15,280
I think the world at large looked like that, the professional world.

457
00:33:15,280 --> 00:33:18,320
So I have a feeling that whatever...

458
00:33:18,320 --> 00:33:24,400
Had I decided that I wasn't going to just get married and have babies at that point,

459
00:33:24,400 --> 00:33:29,120
which probably if you'd have asked me when I was 15, I'd have told you that is what I was going to do.

460
00:33:29,680 --> 00:33:32,080
I think I was the second generation though.

461
00:33:32,080 --> 00:33:32,800
I see.

462
00:33:32,800 --> 00:33:35,120
Not a whole generation's worth.

463
00:33:35,120 --> 00:33:41,120
I think the women who started five years before me, they were really the pioneers,

464
00:33:41,120 --> 00:33:46,560
whether it was they were the first women in law schools, they were among the few women

465
00:33:47,440 --> 00:33:54,880
in medical school classes, whatever professional track and certainly in PhD programs, especially

466
00:33:54,880 --> 00:33:59,040
in the sciences, they were really the pioneers.

467
00:33:59,040 --> 00:34:00,480
And I feel that...

468
00:34:00,480 --> 00:34:09,120
So when I came in, I felt that I wasn't the only one and that there were role models above me.

469
00:34:09,120 --> 00:34:14,080
Few, yes, but I think you only need one or two to be able...

470
00:34:14,080 --> 00:34:14,720
To blaze that trail.

471
00:34:14,720 --> 00:34:18,320
To feel confident that you belong.

472
00:34:20,320 --> 00:34:22,960
And I would say I had a very supportive mentor.

473
00:34:23,840 --> 00:34:30,000
And even if some of the other professors in the program seemed a little more hostile,

474
00:34:31,200 --> 00:34:34,640
I think I didn't pay as much attention to that at the time.

475
00:34:34,640 --> 00:34:35,360
Very good.

476
00:34:35,360 --> 00:34:43,600
And so I always felt that it was that group before me that really were the pioneers.

477
00:34:43,600 --> 00:34:48,160
You know, I was thinking when we were talking about your studies in London and you mentioned

478
00:34:48,160 --> 00:34:52,400
mathematics and physics, but then you went to psychology and autism.

479
00:34:52,400 --> 00:34:56,640
Was part of turning your back on mathematics and physics because it was male dominated?

480
00:34:56,640 --> 00:34:57,200
No.

481
00:34:57,200 --> 00:34:57,840
It wasn't that.

482
00:34:57,840 --> 00:34:59,040
That wasn't a decision for you.

483
00:34:59,040 --> 00:35:04,000
No, it was actually an extremely honest appraisal of my own experience.

484
00:35:04,000 --> 00:35:10,800
Appraisal of my own skills and depth of understanding and engagement.

485
00:35:10,800 --> 00:35:11,440
Yeah.

486
00:35:11,440 --> 00:35:16,880
So young women out there today thinking about doing a PhD in the sciences,

487
00:35:16,880 --> 00:35:18,000
do you have a message for them?

488
00:35:19,200 --> 00:35:24,400
How do they get to be where Helen Tager-Flossberg is today as one of the truly renowned scientists?

489
00:35:26,560 --> 00:35:32,240
I think what I'm going to say is that the most important thing to do is to develop

490
00:35:32,240 --> 00:35:33,840
time management skills.

491
00:35:34,880 --> 00:35:43,840
If you're not an organized person and if you can't take a block of time and use it most effectively,

492
00:35:45,120 --> 00:35:46,640
it's going to be harder for you.

493
00:35:48,080 --> 00:35:50,640
I think you have to stay focused.

494
00:35:50,640 --> 00:36:01,200
Women are always vulnerable to being asked to take on more administrative responsibilities,

495
00:36:02,080 --> 00:36:11,760
more mentoring of students, more, just more busy work, more of those things so that the

496
00:36:11,760 --> 00:36:13,440
men can get on with their lives.

497
00:36:15,360 --> 00:36:17,440
That I think is still true today.

498
00:36:17,440 --> 00:36:18,560
That has not.

499
00:36:18,560 --> 00:36:21,600
And I would say don't be succumbed.

500
00:36:21,600 --> 00:36:30,880
And I think we often do go along with it because at some level, I think we still feel grateful

501
00:36:33,120 --> 00:36:41,840
that we have these jobs, that we do have this and so therefore we're supposed to say yes.

502
00:36:41,840 --> 00:36:44,400
So you still owe a little bit back or something, which is...

503
00:36:44,400 --> 00:36:44,960
Definitely.

504
00:36:44,960 --> 00:36:45,520
Yeah.

505
00:36:45,520 --> 00:36:55,440
And I think women need to find somebody who will help them stick to the stay focused,

506
00:36:55,440 --> 00:37:01,840
know what is your next step, know what's going to get you to the next step and make sure

507
00:37:01,840 --> 00:37:06,480
that you're devoting a significant proportion of your time to doing that.

508
00:37:07,600 --> 00:37:10,320
But never sacrifice the personal side for that.

509
00:37:10,320 --> 00:37:13,120
Sacrifice the administrative side.

510
00:37:13,120 --> 00:37:19,200
Sacrifice the administrative jobs, but don't sacrifice your personal life.

511
00:37:20,400 --> 00:37:21,280
That was fantastic.

512
00:37:21,280 --> 00:37:22,080
Thank you, by the way.

513
00:37:22,080 --> 00:37:23,280
Oh, thank you, John.

514
00:37:24,560 --> 00:37:26,640
You should be on CBS Morning News.

515
00:37:27,840 --> 00:37:32,000
Actually, my colleague Chuck was on CBS Sunday Morning News last week.

516
00:37:32,000 --> 00:37:32,560
Look at that.

517
00:37:34,080 --> 00:37:39,680
Basically taking this EEG data to argue that it can't be vaccines, guys.

518
00:37:39,680 --> 00:37:49,680
Yeah, right.