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PROFESSOR: In some ways, I won't
be able to compete with

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live demonstrations of children
from last week.

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But I will try to talk about
adult development.

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And we will really sweep through
your minds and brains

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from when you were not yet born
until you're going to be

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00:00:45,890 --> 00:00:47,590
in your '90s.

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So here's your life from the
beginning to the end viewed in

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different ways.

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00:00:54,980 --> 00:00:57,250
And we'll touch on a number
of different topics.

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00:00:57,250 --> 00:00:59,930
So you know this question about
people have talked for a

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long time about the development
that one goes

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throughout one's life.

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What walks on four legs in the
morning, two legs in the

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afternoon, three legs
in the evening?

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You know the answer
to this, right?

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People.

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00:01:11,330 --> 00:01:14,040
They're crawling, they're
standing up, and then

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you get to my age.

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And we need an extra little
prop to move around

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successfully.

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00:01:18,880 --> 00:01:21,880
So sort of thinking about this,
that different things

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matter to people at different
ages, that there's different

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priorities, different
ways of thought.

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Erik Erickson is often given
credit for trying to

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articulate that.

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And we'll just walk through
it for a moment.

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Where he said at different
ages, at infancy, early

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childhood, through school,
adolescence, young adulthood,

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people are dealing with
different kinds of issues and

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different developmental tasks
in front of them.

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00:01:46,010 --> 00:01:47,800
Your life is a constant
development.

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00:01:47,800 --> 00:01:50,870
Not maybe as dramatic as infancy
where we saw last time

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00:01:50,870 --> 00:01:53,400
that children really see
the world differently.

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But there's different
challenges in front

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of you at all ages.

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At infancy, you're deciding
who can you

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trust, who can you love.

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Is it a good world?

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00:02:03,520 --> 00:02:08,860
And then the drama of potty
training, independence.

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How much are you becoming a
free agent in the world?

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Early school, where you start
to interact with other

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children, and play, and make
friendships, and think about

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social groups.

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00:02:19,910 --> 00:02:22,870
Later in schools, you're
becoming more advanced in

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terms of what you're learning in
school and more complex in

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terms of the social networks
that you're developing.

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We'll come back to this at the
end, a period of high anxiety

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and drama of adolescents.

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Then there's something about
young adulthood.

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You may have heard recently
people are speculating that

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what used to be the beginning of
young adulthood culturally,

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at least in the US, and maybe
Europe, and industrialized

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parts of the world, that whereas
the '20s used to be

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considered a decade of
adulthood, there are now

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theories floating around or
impressions floating around

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that '20s are the
new adolescence.

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What are you guys think?

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Everybody says, oh my '20s, I'm
going to discover this and

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discover that.

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But when I get to 30, that's
when we're playing for keeps.

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Is it?

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Well, and part of it's because
you live longer, on average.

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Or you count on living longer.

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And you do, on average,
live longer.

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For a person who's counting on
living to 90, which many of

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you are sort of, another decade
of finding your way,

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your 20s, seems reasonable.

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In a world where people didn't
live nearly as long, didn't

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have as many options, by the
time you finished college--

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or many people didn't go to
college-- it's roll up your

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sleeves and get to adulthood.

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So there's all these sort of
magazine discussions, are the

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20s the new teens in terms of
whether people feel they have

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responsibilities they have to
execute as a young adult.

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And this a little bit timed
also, a little bit

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anachronistic, then
having a family.

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Although, I think we're much
more thinking about that's not

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necessarily the root for
everybody at all.

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And then old age where
you give other

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people lots of advice.

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So we're going to talk about
brain development from infancy

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to young adulthood, cognitive
stability

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and decline in adulthood.

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We've talked a little
bit about that.

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We'll talk a bit more.

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Alterations in hemispheric
specializations

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that come with aging.

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A bunch of remarkable results
about exercise in the brain.

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All of us want as we get older,
or just even when

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you're younger maybe, just
a pill you pop and

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you're ready to go.

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That would be the best.

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It turns out there's remarkable
evidence about what

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physical exercise does
for the brain.

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I'll share that with you--
especially in regards to

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aging, but at all ages--

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ideas about how as you get
older, your social and

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emotional goals will tend to
change, a little bit about

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rewards, and a little bit about
back to adolescence and

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some thoughts about what's going
on in the adolescent

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mind and brain.

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So we know if there's one thing
about the brain that's

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stunning, and challenging to
grasp, and empowers us to be

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humans, it's this complexity.

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There's a huge number of
neurons, fantastic number of

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connections among the neurons.

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So there's just a phenomenal
complexity that all starts

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with a single cell.

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And how does the brain
become this

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dramatically complex organ?

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And how does it organize in the
right way to let you be an

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effective learner, an effective
partner in your

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family, and so on?

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So we start with the idea of
neurogenesis, a magical word,

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the neurons being born.

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And they have to make this
crawl, there's a huge path the

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size of a neuron from the
ventricular surface, the

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00:05:40,920 --> 00:05:44,110
ventricle, the fluid-filled
space, to get to the place

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you're going to be
in the brain.

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It's a huge adventure
per neuron.

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Cells dividing there, the
earliest neurons are existing

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by the second embryonic week.

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So that's when you began
to produce your

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neurons in your brain.

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By the seventh embryonic week--
so you're just two

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months of pregnancy--

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you're producing an estimated
500,000 neurons a minute.

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We said the neuron is kind of
like a moderate computer.

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Except unlike iPhones, it can't
keep track of where

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you're going all the time.

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We said it's a moderate
computer.

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So 500,000 of those every
minute, I mean, staggering.

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That it all works out
is staggering.

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By the 18th week, you've mostly
made all the neurons

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you're ever going to make for
the rest of your life except

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in two brain regions.

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And there's been a big debate
in the last decade about

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00:06:36,960 --> 00:06:37,680
another brain region.

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I'll share those with you.

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00:06:38,910 --> 00:06:41,290
But people have been taught for
many, many, many years in

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medical school, and college, and
graduate school, that all

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the neurons you get are
by the 18th week.

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So hang on to them
through healthy

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living and wise behavior.

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Because you have what
you have, right?

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So don't lose them.

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But we'll talk about that
you lose the vast

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majority of them anyway.

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I still recommend
healthy living.

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Because you know, perhaps from
other courses, that the brain

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does this wild thing.

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It excessively overproduces, by
massive scales, the number

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of neurons and the connections
among the neurons.

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And then through use, it gets
rid of neurons and gets rid of

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connections among neurons.

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It's exactly the opposite way
if you build a building.

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If you build a building,
what do you do?

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You construct every bit of it
you need, and you're done.

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Well you don't do is say, I
need a two-story building.

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So I'm going to do a 40-story
building or a 90-story

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building and then knock
off the stories

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as they're not needed.

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You say, well, that's wild.

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Why would I do that?

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But the brain brilliantly makes
many more neurons and

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many more connections on epic
scales and then only uses the

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ones that seem to be
useful for the

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functions of the brain.

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And so for that reason, the
density of the neurons in the

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brain is much higher in a
two-year-old than in you,

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where it was much higher when
you were two than it is now.

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So in a two-year-old, they
have 55% more gray matter

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density in the frontal
lobe than an adult.

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Even at age five, even
at age seven,

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they're 10% percent more.

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From a peak of around before
birth, you're constantly

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shedding neurons and their
connections and keeping the

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ones that seem to be
effective somehow.

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Now, for many years people said,
is there neurogenesis in

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the adult brain?

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Is everything you get before
you're born and

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that's pretty much it?

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And there's many reasons to
be interested in that.

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One is just how does
the brain work?

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How do people work?

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The second is for diseases
like Alzheimer's disease,

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Parkinson's disease,
and other diseases.

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We would love to replace neurons
that have died to help

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people do better.

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So can the brain make new
neurons before birth?

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There's compelling evidence in
animals, and some indirect

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evidence in people too, that
neurogenesis does continue

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into adulthood in the olfactory
bulb and in this

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00:09:01,980 --> 00:09:03,752
particular part-- and I'll come
back to this-- in the

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hippocampus, a small part of
the hippocampus called the

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dentate gyrus.

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Everybody's in pretty much
agreement on this for the

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moment, which is kind
of interesting.

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Why those two areas amongst all
the areas in the brain?

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What makes them different that
they can produce neurons all

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throughout your life?

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00:09:20,140 --> 00:09:22,370
And then about a decade ago,
Elizabeth Gould at Princeton

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said, oh, when I do the right
kind of experiment, I see new

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neurons in the prefrontal cortex
of monkeys, and for

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00:09:30,232 --> 00:09:31,320
human primates.

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That was a giant revolution.

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00:09:34,250 --> 00:09:35,500
Because they said,
wait a minute.

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Maybe if monkeys are doing it,
people might be doing it,

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making neurons throughout
their life.

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00:09:41,100 --> 00:09:41,950
We just did know that.

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It's not so easy to measure.

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If you think about it, the kind
of experiment to know for

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00:09:45,980 --> 00:09:50,440
certain if a human is making a
new neuron is not so easy.

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00:09:50,440 --> 00:09:52,020
Because brain imaging
is very far from the

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single neuron level.

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And even if we saw a neuron,
how could we tell it's new?

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And then Pasko Rakic, a big
developmental researcher at

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00:10:01,090 --> 00:10:04,360
Yale said, that what she
really saw was glia.

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The glia are the other cells in
the brain, not the neurons.

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They support the neurons.

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00:10:09,460 --> 00:10:13,240
Everybody agrees that you make
glia all through your life.

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There's no debate about that.

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00:10:14,600 --> 00:10:16,990
But glia are not the stuff
of thoughts and feelings.

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Neurons are.

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00:10:18,390 --> 00:10:21,470
So what do we understand
about that whole story?

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Here is an unbelievable
experiment, I think.

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It's really not an experiment.

235
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But it's a measurement.

236
00:10:29,550 --> 00:10:33,770
Published in 2006, it's one
approach to asking, do adults

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00:10:33,770 --> 00:10:35,570
make new neurons?

238
00:10:35,570 --> 00:10:38,900
So the nuclear bomb tests that
occur during the Cold War sent

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00:10:38,900 --> 00:10:43,090
a carbon-14 into the atmosphere
from 1955 to 1963

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00:10:43,090 --> 00:10:45,380
until there was an international
test ban treaty.

241
00:10:45,380 --> 00:10:47,660
And then these decreased
and stopped.

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00:10:47,660 --> 00:10:50,350
But there was a lot of nuclear
bomb testing in the

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00:10:50,350 --> 00:10:52,410
late '50s and '60s.

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00:10:52,410 --> 00:10:55,380
That released carbon-14
into the atmosphere.

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00:10:55,380 --> 00:10:58,530
And that integrates with DNA and
forms a date mark for the

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00:10:58,530 --> 00:10:59,600
cell of a birth.

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00:10:59,600 --> 00:11:02,850
So this is not an experiment
we would want to do again,

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00:11:02,850 --> 00:11:05,210
atmospheric nuclear testing,
and having nuclear stuff

249
00:11:05,210 --> 00:11:07,810
floating around in
the atmosphere.

250
00:11:07,810 --> 00:11:09,340
I'll tell you the bottom line,
and I'll show you how they

251
00:11:09,340 --> 00:11:10,820
figured this out.

252
00:11:10,820 --> 00:11:13,370
What they figured out is looking
at people who died a

253
00:11:13,370 --> 00:11:15,170
few years ago, that

254
00:11:15,170 --> 00:11:16,850
nonneuronal cells are generated.

255
00:11:16,850 --> 00:11:19,200
That was found before glial
cells are made throughout your

256
00:11:19,200 --> 00:11:21,080
lifetime is the inference
from the finding.

257
00:11:21,080 --> 00:11:24,580
But neurons are not generated
in adult neocortex.

258
00:11:24,580 --> 00:11:29,140
The commentary in this article
said, no new neurons for you.

259
00:11:29,140 --> 00:11:30,110
OK, that's not quite true.

260
00:11:30,110 --> 00:11:32,570
We know these two little areas
in the brain do it but not in

261
00:11:32,570 --> 00:11:33,720
most of the brain.

262
00:11:33,720 --> 00:11:37,060
And they also looked at
something called BrdU,

263
00:11:37,060 --> 00:11:39,070
B-R-D-U, which is another
way to take a

264
00:11:39,070 --> 00:11:41,510
brain if you have it.

265
00:11:41,510 --> 00:11:43,700
It marks newly synthesized
DNA.

266
00:11:43,700 --> 00:11:46,030
So if you have the brain
directly to measure it, you

267
00:11:46,030 --> 00:11:48,530
have a couple of measures of
newly synthesized DNA, which

268
00:11:48,530 --> 00:11:51,090
would be the marker
of new neurons.

269
00:11:51,090 --> 00:11:52,670
So here's a fantastically
interesting thing.

270
00:11:52,670 --> 00:11:55,080
They took people who were born
in different times, took

271
00:11:55,080 --> 00:11:59,580
postmortem samples, and measured
carbon-14 relative to

272
00:11:59,580 --> 00:12:00,400
what was expected--

273
00:12:00,400 --> 00:12:03,430
there's a line here-- it was
relative to what was expected

274
00:12:03,430 --> 00:12:05,400
by the amount of carbon
in the atmosphere.

275
00:12:08,250 --> 00:12:09,580
And here's what they found.

276
00:12:09,580 --> 00:12:13,320
If they look for somebody born
after 1963, they have, in

277
00:12:13,320 --> 00:12:16,820
their neurons, exactly the
amount that you would expect

278
00:12:16,820 --> 00:12:22,350
if they made all their neurons
around here and the decrease

279
00:12:22,350 --> 00:12:25,320
here didn't affect the
neurons at all.

280
00:12:25,320 --> 00:12:28,920
The glia are here, which is kind
of an average of here and

281
00:12:28,920 --> 00:12:29,800
the rest of life.

282
00:12:29,800 --> 00:12:33,610
So if you measure the average
age of the glia, it was about

283
00:12:33,610 --> 00:12:35,800
the average age of the life of
the person the carbon was

284
00:12:35,800 --> 00:12:38,870
being picked up in the DNA,
because it's being made.

285
00:12:38,870 --> 00:12:40,400
It's being kept,
and being made.

286
00:12:40,400 --> 00:12:44,700
But the neurons all looked like
one value, the value that

287
00:12:44,700 --> 00:12:47,500
has to do with when
you're born.

288
00:12:47,500 --> 00:12:50,980
So it's not changing the number
of neurons that are

289
00:12:50,980 --> 00:12:52,770
showing the carbon-14.

290
00:12:52,770 --> 00:12:54,910
As if whatever you've got
at birth, that's it.

291
00:12:54,910 --> 00:12:58,450
On the other hand, here is
somebody born before 1963,

292
00:12:58,450 --> 00:13:02,130
having essentially zero carbon
that's being showing up in

293
00:13:02,130 --> 00:13:05,340
their neuronal DNA, and having
again the expected average

294
00:13:05,340 --> 00:13:08,150
glial DNA as if glia
kept going.

295
00:13:08,150 --> 00:13:09,100
So this is fantastic.

296
00:13:09,100 --> 00:13:11,610
It's looking at the carbon-14
in the DNA of neurons and

297
00:13:11,610 --> 00:13:13,620
glial of people who
have passed away.

298
00:13:13,620 --> 00:13:17,120
And saying the carbon-14 dating
looks like neurons.

299
00:13:17,120 --> 00:13:18,500
You get them all before
you're born.

300
00:13:18,500 --> 00:13:19,080
That's it.

301
00:13:19,080 --> 00:13:20,970
Glia, you keep making.

302
00:13:20,970 --> 00:13:23,830
And they can look at it more
directly by looking at this

303
00:13:23,830 --> 00:13:27,260
thing that shows you recent
DNA, again, showing you

304
00:13:27,260 --> 00:13:31,140
impressively that glia keep
making new glia with new DNA

305
00:13:31,140 --> 00:13:33,170
but not new neurons.

306
00:13:33,170 --> 00:13:35,380
So the current conclusion in the
field, as far as anybody

307
00:13:35,380 --> 00:13:38,860
can tell, is no new neurons for
you except in your dentate

308
00:13:38,860 --> 00:13:42,780
gyrus and olfactory bulb.

309
00:13:42,780 --> 00:13:45,060
Now here's something
fantastic though.

310
00:13:45,060 --> 00:13:46,540
It appears that exercise--

311
00:13:46,540 --> 00:13:48,980
I'll just show you one example
in animals and humans--

312
00:13:48,980 --> 00:13:52,790
there's evidence that exercise
will pump up the number of new

313
00:13:52,790 --> 00:13:55,060
neurons you make in the
dentate gyrus of the

314
00:13:55,060 --> 00:13:56,330
hippocampus.

315
00:13:56,330 --> 00:13:57,290
And we know that the
hippocampus is

316
00:13:57,290 --> 00:13:58,200
important for memory.

317
00:13:58,200 --> 00:14:00,850
So that's not a bad place
to make new neurons.

318
00:14:00,850 --> 00:14:03,340
So you know that going to
exercise will strengthen you

319
00:14:03,340 --> 00:14:04,270
in various ways.

320
00:14:04,270 --> 00:14:06,490
But you never realized, unless
you follow this line of work,

321
00:14:06,490 --> 00:14:09,890
that when you exercise, you're
enhancing the number of new

322
00:14:09,890 --> 00:14:13,180
neurons that you're producing
in your dentate gyrus.

323
00:14:13,180 --> 00:14:16,700
So here's a couple ways people
have approached this.

324
00:14:16,700 --> 00:14:18,905
So one way is to measure
cerebral blood volume, how

325
00:14:18,905 --> 00:14:20,480
much blood is in the dentate.

326
00:14:20,480 --> 00:14:23,780
And I'm going to show you
evidence that mice that are

327
00:14:23,780 --> 00:14:27,800
allowed to exercise push
up the blood volume.

328
00:14:27,800 --> 00:14:29,860
And that seems to go with
direct evidence of

329
00:14:29,860 --> 00:14:30,430
neurogenesis.

330
00:14:30,430 --> 00:14:31,890
Because you can do that
in the animals.

331
00:14:31,890 --> 00:14:34,200
You can look up sacrificed
animals.

332
00:14:34,200 --> 00:14:37,010
And then in humans, some
indirect evidence that

333
00:14:37,010 --> 00:14:39,970
exercise is, again, pushing
up the blood volume in the

334
00:14:39,970 --> 00:14:42,590
dentate and pushing up a little
bit of memory abilities

335
00:14:42,590 --> 00:14:44,010
that go with the part
of the brain.

336
00:14:44,010 --> 00:14:48,060
We can't go in and measure
neurons in the humans.

337
00:14:48,060 --> 00:14:51,210
So here are mice who exercise
or didn't exercise.

338
00:14:51,210 --> 00:14:52,980
They measured the
blood volume.

339
00:14:52,980 --> 00:14:56,350
Here in red is the dentate
part of the hippocampus.

340
00:14:56,350 --> 00:15:00,060
You can see it's the hottest
spot for blood volume.

341
00:15:00,060 --> 00:15:03,390
And it's the only part that
responds to exercise.

342
00:15:03,390 --> 00:15:05,780
So they had some mice
not get to exercise,

343
00:15:05,780 --> 00:15:07,780
some mice get to exercise.

344
00:15:07,780 --> 00:15:10,150
The blood volume increases
within the hippocampus

345
00:15:10,150 --> 00:15:13,050
selectively in a small component
of the hippocampus,

346
00:15:13,050 --> 00:15:14,040
the dentate gyrus.

347
00:15:14,040 --> 00:15:16,700
Exercise is pushing up
the blood volume.

348
00:15:16,700 --> 00:15:18,470
Now that's not direct evidence
about what's happening at the

349
00:15:18,470 --> 00:15:19,460
cellular level.

350
00:15:19,460 --> 00:15:22,840
But they can sacrifice these
animals and show you that if

351
00:15:22,840 --> 00:15:26,080
you look at this binding that
goes with new neurons, with

352
00:15:26,080 --> 00:15:29,750
new DNA, that's pushed up
the exercise animals.

353
00:15:29,750 --> 00:15:31,160
Here's the statistics.

354
00:15:31,160 --> 00:15:32,980
Here's the picture.

355
00:15:32,980 --> 00:15:37,090
So in the animals, they can
correlate directly.

356
00:15:37,090 --> 00:15:41,070
More blood volume and more new
neurons going with more

357
00:15:41,070 --> 00:15:41,960
physical exercise.

358
00:15:41,960 --> 00:15:44,690
In humans, they can measure
the blood volume.

359
00:15:44,690 --> 00:15:46,790
And so they had some people do
more exercise, some people

360
00:15:46,790 --> 00:15:47,580
less exercise.

361
00:15:47,580 --> 00:15:49,870
Again, it was a dentate
gyrus selectively.

362
00:15:49,870 --> 00:15:53,930
It showed an increase in
blood volume in humans.

363
00:15:53,930 --> 00:15:55,280
And now they give them
a memory test.

364
00:15:55,280 --> 00:15:56,900
And it's not overwhelming.

365
00:15:56,900 --> 00:15:59,570
But at least in some cases, the
people who did exercising,

366
00:15:59,570 --> 00:16:02,230
who pushed up their blood
volume, also pushed up a

367
00:16:02,230 --> 00:16:04,930
little bit their memory
performance.

368
00:16:04,930 --> 00:16:07,840
So in humans it has to be more
indirect, but all the data

369
00:16:07,840 --> 00:16:11,370
aligned with the idea that
exercise is pushing up your

370
00:16:11,370 --> 00:16:14,200
own neuronal genesis, the
creation of new neurons in one

371
00:16:14,200 --> 00:16:16,700
of the two regions everybody
agrees we make new neurons,

372
00:16:16,700 --> 00:16:18,960
the dentate gyrus and
the hippocampus.

373
00:16:21,920 --> 00:16:24,350
But cells have to go incredible
distances at the

374
00:16:24,350 --> 00:16:25,250
cellular size.

375
00:16:25,250 --> 00:16:26,800
Neurons have to travel to
the intended location.

376
00:16:26,800 --> 00:16:29,720
Migration occurs over many
months including eight months

377
00:16:29,720 --> 00:16:30,650
postnatally.

378
00:16:30,650 --> 00:16:33,780
Here's this neuron following
it's little path to where it's

379
00:16:33,780 --> 00:16:35,820
going to go.

380
00:16:35,820 --> 00:16:39,500
There's glial tracks following
molecular cues as to their

381
00:16:39,500 --> 00:16:41,920
ultimate target location
to get organized.

382
00:16:41,920 --> 00:16:44,380
Its initial destination and
function are predetermined at

383
00:16:44,380 --> 00:16:45,190
the start of the migration.

384
00:16:45,190 --> 00:16:47,940
People can measure things in
these that tell you where this

385
00:16:47,940 --> 00:16:48,520
is going to end up.

386
00:16:48,520 --> 00:16:51,240
It's programed in these cells.

387
00:16:51,240 --> 00:16:54,260
Unless there's something that
blocks them, they know where

388
00:16:54,260 --> 00:16:55,480
they're going to go and
make up different

389
00:16:55,480 --> 00:16:57,970
parts of the brain.

390
00:16:57,970 --> 00:17:00,830
And then they form synapses, the
part where information is

391
00:17:00,830 --> 00:17:03,310
sent from one neuron
to another.

392
00:17:03,310 --> 00:17:05,859
It occurs throughout the brain,
but at different rates

393
00:17:05,859 --> 00:17:06,970
and different areas.

394
00:17:06,970 --> 00:17:10,500
So very early, you see
it in spinal cord.

395
00:17:10,500 --> 00:17:13,420
Very late, you see it in higher
cortical areas like

396
00:17:13,420 --> 00:17:15,079
prefrontal cortex.

397
00:17:15,079 --> 00:17:17,470
At the peak growth, there's an
estimate-- these are all gross

398
00:17:17,470 --> 00:17:18,290
estimates--

399
00:17:18,290 --> 00:17:23,280
that you may be forming 1.8
million synapses per second.

400
00:17:23,280 --> 00:17:26,910
It's stunning, 1.8 million
synapses per second.

401
00:17:26,910 --> 00:17:29,510
And do you know how many
molecules are in an average

402
00:17:29,510 --> 00:17:31,990
synapse by current
estimations?

403
00:17:31,990 --> 00:17:32,970
1,000.

404
00:17:32,970 --> 00:17:35,860
There's 1,000 different
molecules in a synapse for it

405
00:17:35,860 --> 00:17:37,300
to do it has to do.

406
00:17:37,300 --> 00:17:39,660
Multiply that times 1.8
million per second.

407
00:17:39,660 --> 00:17:43,210
It's spectacular biology.

408
00:17:43,210 --> 00:17:45,140
And then they keep getting more
and more until two years.

409
00:17:45,140 --> 00:17:46,600
And then you start
just losing them.

410
00:17:46,600 --> 00:17:48,770
By age 16, you'll have
lost a lot of them.

411
00:17:48,770 --> 00:17:50,650
And so the people have this
idea we mentioned before,

412
00:17:50,650 --> 00:17:51,640
pruning and selection.

413
00:17:51,640 --> 00:17:54,130
That we overgrow the number
of neurons, the number of

414
00:17:54,130 --> 00:17:55,170
connections.

415
00:17:55,170 --> 00:17:57,640
What stays is activity
dependence, or this use it or

416
00:17:57,640 --> 00:17:59,380
lose it neural Darwinism.

417
00:17:59,380 --> 00:18:00,560
Here's something amazing.

418
00:18:00,560 --> 00:18:04,770
There's an estimate that we lose
20 billion synapses per

419
00:18:04,770 --> 00:18:06,910
day through adolescence.

420
00:18:06,910 --> 00:18:09,060
And that's not a bad thing.

421
00:18:09,060 --> 00:18:10,920
That's not the worst behaving
adolescents doing the worst

422
00:18:10,920 --> 00:18:12,020
things they can do.

423
00:18:12,020 --> 00:18:14,470
That's the brain getting rid of

424
00:18:14,470 --> 00:18:17,420
connections that aren't useful.

425
00:18:17,420 --> 00:18:19,090
It's an incredibly interesting
way to

426
00:18:19,090 --> 00:18:20,670
construct a powerful brain.

427
00:18:20,670 --> 00:18:23,950
It's to get everybody
to way overbuild.

428
00:18:23,950 --> 00:18:27,260
And then eliminate the ones that
aren't powerfully useful.

429
00:18:30,260 --> 00:18:33,570
And another marker of
development is myelination.

430
00:18:33,570 --> 00:18:36,720
That's the growth of the fatty
sheath that surrounds the

431
00:18:36,720 --> 00:18:38,050
neurons that are extending
distances.

432
00:18:38,050 --> 00:18:40,740
It insulates them and
accelerates their signal.

433
00:18:40,740 --> 00:18:45,110
It looks like white matter
in the postmortem brain.

434
00:18:45,110 --> 00:18:46,580
What happens through
adolescence--

435
00:18:46,580 --> 00:18:48,000
here's age four to 22--

436
00:18:48,000 --> 00:18:55,260
is that white matter goes up,
and gray matter goes down.

437
00:18:55,260 --> 00:18:57,990
So quite interesting, the total
brain size from about

438
00:18:57,990 --> 00:19:01,100
age six to about 20-- young
adulthood, most of you--

439
00:19:01,100 --> 00:19:03,770
stays about the same, the
total brain size.

440
00:19:03,770 --> 00:19:06,440
What you're doing is you're
getting rid of gray matter.

441
00:19:06,440 --> 00:19:07,870
And you're enhancing
white matter.

442
00:19:07,870 --> 00:19:09,800
You're getting rid of the
neurons that are nonproductive

443
00:19:09,800 --> 00:19:11,850
and the synapses that
are nonproductive.

444
00:19:11,850 --> 00:19:13,810
And you're increasing the
strength with which different

445
00:19:13,810 --> 00:19:15,840
parts of the brain can
communicate with one another

446
00:19:15,840 --> 00:19:18,610
through the white matter.

447
00:19:18,610 --> 00:19:21,610
And so here's the kinds of
pictures of this growth.

448
00:19:21,610 --> 00:19:25,070
And some of the parts of the
brain that mature latest by

449
00:19:25,070 --> 00:19:27,990
these kinds of measures of
getting rid of the overgrowth,

450
00:19:27,990 --> 00:19:29,180
are in prefrontal cortex.

451
00:19:29,180 --> 00:19:30,430
And we've talked about
that before.

452
00:19:34,150 --> 00:19:36,720
So many people are interested
always in thinking about

453
00:19:36,720 --> 00:19:38,170
developmental issues and
the biology of them.

454
00:19:38,170 --> 00:19:39,970
And here's a kind of
a stunning finding.

455
00:19:39,970 --> 00:19:42,500
And we don't know exactly how
it would relate to humans.

456
00:19:42,500 --> 00:19:43,900
But I thought it would be
interesting to share with you

457
00:19:43,900 --> 00:19:45,920
and think about this
just a little bit.

458
00:19:45,920 --> 00:19:48,920
So the title of the paper in
science was "Good Memories of

459
00:19:48,920 --> 00:19:53,360
Bad Events in Infancy." So we
know from before, and just

460
00:19:53,360 --> 00:19:56,040
common sense, that fear is
important for the survival.

461
00:19:56,040 --> 00:19:57,940
So we start at the amygdala,
which seems essential for

462
00:19:57,940 --> 00:20:00,540
learning what's to be feared.

463
00:20:00,540 --> 00:20:02,720
Because what's to be feared is
what injures you, or worst

464
00:20:02,720 --> 00:20:05,100
case, could kill you.

465
00:20:05,100 --> 00:20:07,670
So the amygdala is essential
for learned fear.

466
00:20:07,670 --> 00:20:10,110
And we know that one example, a
fear condition that depends

467
00:20:10,110 --> 00:20:11,050
on the amygdala, would
be a neutral

468
00:20:11,050 --> 00:20:13,220
stimulus like an odor--

469
00:20:13,220 --> 00:20:16,650
odor that's not particularly
good or bad, just an odor--

470
00:20:16,650 --> 00:20:19,420
and then a shock that makes
an aversive stimulus.

471
00:20:19,420 --> 00:20:21,640
So you pair them through
conditioning, odor, shock,

472
00:20:21,640 --> 00:20:22,240
odor, shock.

473
00:20:22,240 --> 00:20:24,530
So the odor predicts
the shock.

474
00:20:24,530 --> 00:20:29,640
Now, they looked at young rats
and looked at attachments.

475
00:20:29,640 --> 00:20:31,310
And here's what they find
kind of remarkably.

476
00:20:31,310 --> 00:20:35,250
Up to postnatal day nine for
these rats, if they were

477
00:20:35,250 --> 00:20:38,920
exposed to the odors and the
shocks, here's what they do.

478
00:20:38,920 --> 00:20:42,300
They know through pairings
odor, shock, odor, shock,

479
00:20:42,300 --> 00:20:44,410
odor, shock, here
comes the odor.

480
00:20:44,410 --> 00:20:45,660
Here comes the shock.

481
00:20:45,660 --> 00:20:47,700
They still approach the odors.

482
00:20:47,700 --> 00:20:48,710
That's what's in this graph.

483
00:20:48,710 --> 00:20:51,780
Up to nine days, the
rats, the mice--

484
00:20:51,780 --> 00:20:53,240
sorry--

485
00:20:53,240 --> 00:20:57,410
are still approaching this odor
even though it will lead

486
00:20:57,410 --> 00:20:58,950
to a shock.

487
00:20:58,950 --> 00:21:01,490
But on the 10th day,
just one day later,

488
00:21:01,490 --> 00:21:02,710
it completely reverses.

489
00:21:02,710 --> 00:21:04,920
And they avoid the odors
that predict the

490
00:21:04,920 --> 00:21:07,070
shock, a complete reversal.

491
00:21:07,070 --> 00:21:08,790
So they keep going to the
odors with the shock.

492
00:21:08,790 --> 00:21:13,610
And on the 10th today, the
pups stop going there.

493
00:21:13,610 --> 00:21:15,030
And what they also
find is this.

494
00:21:15,030 --> 00:21:19,280
If they look at metabolic
activity in the amygdala, for

495
00:21:19,280 --> 00:21:21,890
the nine-day olds, it's the
same for the odor and the

496
00:21:21,890 --> 00:21:23,490
shock, where a neutral order.

497
00:21:23,490 --> 00:21:25,970
It's not selective to
what's to be feared.

498
00:21:25,970 --> 00:21:29,270
And the 10-day old, here's a big
response in the amygdala

499
00:21:29,270 --> 00:21:32,710
for the odor that predicts the
shock, for the fearful

500
00:21:32,710 --> 00:21:34,710
learning, to know what's
scary, and

501
00:21:34,710 --> 00:21:37,610
injurious and dangerous.

502
00:21:37,610 --> 00:21:39,090
So how do people think
about this?

503
00:21:39,090 --> 00:21:42,100
Well, this is an animal
experiment up to nine days.

504
00:21:42,100 --> 00:21:46,060
We can't really know how
it relates to people.

505
00:21:46,060 --> 00:21:47,970
But the speculation was this.

506
00:21:47,970 --> 00:21:49,680
And maybe there's something
to it on a

507
00:21:49,680 --> 00:21:50,990
different scale on people.

508
00:21:50,990 --> 00:21:57,210
Why would an animal approach
something injurious, up to the

509
00:21:57,210 --> 00:21:59,330
amygdala seems to get more
mature, and then

510
00:21:59,330 --> 00:22:00,560
avoid what's injurious.

511
00:22:00,560 --> 00:22:04,230
Why would that happen in such
a predictable evolutionary

512
00:22:04,230 --> 00:22:06,700
determined way?

513
00:22:06,700 --> 00:22:08,780
And the hypothesis is this.

514
00:22:08,780 --> 00:22:14,260
That if you're a very helpless
newborn, you have to go to

515
00:22:14,260 --> 00:22:16,630
things no matter what.

516
00:22:16,630 --> 00:22:18,930
Because you're so dependent
on things in your

517
00:22:18,930 --> 00:22:21,240
environment to survive.

518
00:22:21,240 --> 00:22:24,190
But at some moment you mature
enough that you

519
00:22:24,190 --> 00:22:25,390
say no thank you.

520
00:22:25,390 --> 00:22:27,660
If it's going to be shocking
and painful, I'm

521
00:22:27,660 --> 00:22:28,870
going to avoid it.

522
00:22:28,870 --> 00:22:31,220
You become kind of independent
in that sense, in

523
00:22:31,220 --> 00:22:32,730
the concrete sense.

524
00:22:32,730 --> 00:22:35,290
And so the author said, well,
could it be helpful for

525
00:22:35,290 --> 00:22:39,400
newborns to know, no matter
what, approach a caregiver,

526
00:22:39,400 --> 00:22:41,570
not respond to things that are
negative, because you need the

527
00:22:41,570 --> 00:22:44,110
care, because you're
so dependent.

528
00:22:44,110 --> 00:22:46,530
And now this is super
speculatively.

529
00:22:46,530 --> 00:22:49,130
A thing that's been noted is
that even in families where

530
00:22:49,130 --> 00:22:52,900
there's unfortunate tremendous
abuse for a young child, the

531
00:22:52,900 --> 00:22:56,550
abuse victims so commonly
remain powerful

532
00:22:56,550 --> 00:22:57,760
loyal to their parents.

533
00:22:57,760 --> 00:23:01,540
Is this kind of a mechanism that
mixes up attachment and

534
00:23:01,540 --> 00:23:04,850
fear especially when you're
young and can't separate them

535
00:23:04,850 --> 00:23:06,060
out so well?

536
00:23:06,060 --> 00:23:08,840
So it's a huge leap from
the mice to the people.

537
00:23:08,840 --> 00:23:10,780
But it's a mechanism that we
can understand might be

538
00:23:10,780 --> 00:23:13,920
involved in how attachment
and fear can have unusual

539
00:23:13,920 --> 00:23:16,560
relationships with
one another.

540
00:23:16,560 --> 00:23:18,510
All right.

541
00:23:18,510 --> 00:23:22,010
You can't avoid reading in the
newspapers, or seeing on your

542
00:23:22,010 --> 00:23:25,410
computer screen, discussions
about the deficit and older

543
00:23:25,410 --> 00:23:29,200
people like me demanding a lot
of medical care that's paid

544
00:23:29,200 --> 00:23:33,710
for by the wages you're going
to get in a couple years.

545
00:23:33,710 --> 00:23:34,960
I mean that's how
I look at it.

546
00:23:38,020 --> 00:23:42,060
So you are entering a world,
we're all entering a world,

547
00:23:42,060 --> 00:23:45,880
where the changing ages
demography of our society is

548
00:23:45,880 --> 00:23:46,850
spectacular.

549
00:23:46,850 --> 00:23:48,730
Japan is ahead of us in
this a little bit.

550
00:23:48,730 --> 00:23:50,260
The rest of the world
is following.

551
00:23:50,260 --> 00:23:51,980
And China is going to
be unbelievable when

552
00:23:51,980 --> 00:23:53,490
it happens on scale.

553
00:23:53,490 --> 00:23:56,000
But the United States right
now, right now.

554
00:23:56,000 --> 00:23:57,150
And here's why.

555
00:23:57,150 --> 00:24:00,640
For most of human history, the
average life expectancy was up

556
00:24:00,640 --> 00:24:01,310
to 20 years old.

557
00:24:01,310 --> 00:24:02,390
That's why you had
to be an adult.

558
00:24:02,390 --> 00:24:04,550
Because at 20, who knows
how much time I have.

559
00:24:04,550 --> 00:24:07,430
I better do my adult things.

560
00:24:07,430 --> 00:24:08,620
Some people lived
for a long time.

561
00:24:08,620 --> 00:24:09,330
This is really interesting.

562
00:24:09,330 --> 00:24:12,390
It wasn't that everybody
perished by 30.

563
00:24:12,390 --> 00:24:15,690
Some people lived to
60, 70, 80, 90.

564
00:24:15,690 --> 00:24:18,970
But many people fell ill to
many diseases that are now

565
00:24:18,970 --> 00:24:20,670
readily cured.

566
00:24:20,670 --> 00:24:22,704
So the average age was 20.

567
00:24:22,704 --> 00:24:26,680
In the 1800s, it became the
'30s, just a couple hundred

568
00:24:26,680 --> 00:24:28,720
years ago in all of
human history.

569
00:24:28,720 --> 00:24:33,980
By 2000, the average person
in the US lived until 77.

570
00:24:33,980 --> 00:24:36,670
By 2010, 78.

571
00:24:36,670 --> 00:24:40,170
So we're having a spectacular
growth in the proportion of

572
00:24:40,170 --> 00:24:43,580
humans in our society who are
living a long, long time,

573
00:24:43,580 --> 00:24:45,740
which is a wonderful thing.

574
00:24:45,740 --> 00:24:48,190
But it's radically changing the
world we live in and the

575
00:24:48,190 --> 00:24:50,520
world for those people who
are older as well.

576
00:24:50,520 --> 00:24:54,340
So, for example, 100-year-old
people, there's 50,000 of them

577
00:24:54,340 --> 00:24:57,770
in the US, which is triple what
there was a time ago.

578
00:24:57,770 --> 00:25:00,400
And it's expected to be a
million people in the US who

579
00:25:00,400 --> 00:25:03,980
are 100 years and older by
2050, which is in your

580
00:25:03,980 --> 00:25:07,680
lifetime, a million people
in the US alone

581
00:25:07,680 --> 00:25:10,800
will be 100 or older.

582
00:25:10,800 --> 00:25:15,100
And maybe 50% of girls born in
2000 will live for a century.

583
00:25:15,100 --> 00:25:19,400
Spectacular changes are
occurring right this moment.

584
00:25:19,400 --> 00:25:23,680
The baby boom generation, huge
numbers of us are approaching

585
00:25:23,680 --> 00:25:26,170
retirement and the kind of
medical support that gets

586
00:25:26,170 --> 00:25:30,980
heavier when you get older on
average, huge numbers of us.

587
00:25:30,980 --> 00:25:31,700
How's it changing?

588
00:25:31,700 --> 00:25:34,070
One way it's changing is that
families often have-- and you

589
00:25:34,070 --> 00:25:36,555
might hear this-- an issue of
families feeling that they're

590
00:25:36,555 --> 00:25:38,030
a sandwich generation.

591
00:25:38,030 --> 00:25:40,360
They're taking care of their
children and the elderly.

592
00:25:40,360 --> 00:25:43,820
And you can bet if you have
parents who are living to 120,

593
00:25:43,820 --> 00:25:46,600
you're doing that.

594
00:25:46,600 --> 00:25:49,490
Giant effects on education,
pension, work, financial

595
00:25:49,490 --> 00:25:52,140
markets, I mean these are
epic societal effects.

596
00:25:52,140 --> 00:25:54,450
So you're hearing the discussion
now about how the

597
00:25:54,450 --> 00:25:56,860
US is going to deal with this.

598
00:25:56,860 --> 00:25:58,920
So there used to be kind
of an old model.

599
00:25:58,920 --> 00:26:00,010
And even this is not that old.

600
00:26:00,010 --> 00:26:03,030
This is from the mid-1950s.

601
00:26:03,030 --> 00:26:06,900
Your job was to go to college,
have a career, have a mate,

602
00:26:06,900 --> 00:26:09,110
take care of a kid, retire
at 65, and put your

603
00:26:09,110 --> 00:26:10,560
feet up on the desk.

604
00:26:10,560 --> 00:26:12,900
But all of a sudden, if
everybody's living--

605
00:26:12,900 --> 00:26:15,030
not everybody, but huge numbers
of people are living--

606
00:26:15,030 --> 00:26:19,800
until 70, 80, 90, 100, many in
pretty good health-- not

607
00:26:19,800 --> 00:26:22,220
everybody we wish for-- but many
in pretty good health,

608
00:26:22,220 --> 00:26:24,230
that's a fantastically
different thing.

609
00:26:24,230 --> 00:26:26,500
65 is no longer the retirement
moment, and you're

610
00:26:26,500 --> 00:26:27,500
glad you made it.

611
00:26:27,500 --> 00:26:31,440
65 is something like the
halfway point of your

612
00:26:31,440 --> 00:26:34,220
potential work life.

613
00:26:34,220 --> 00:26:38,070
20 to 60, 60 to 100, something
like this.

614
00:26:38,070 --> 00:26:39,560
It's an unbelievable change.

615
00:26:39,560 --> 00:26:42,450
You cannot overestimate how it's
changing the world around

616
00:26:42,450 --> 00:26:45,030
you, and how it will affect the
economics and the politics

617
00:26:45,030 --> 00:26:49,230
of the world that the rest of us
will be in for many years.

618
00:26:49,230 --> 00:26:52,070
There's about 10% of the
population over 65 now.

619
00:26:52,070 --> 00:26:56,100
In 20 years, one out of every
four people will be over 65 by

620
00:26:56,100 --> 00:26:57,850
current estimates.

621
00:26:57,850 --> 00:27:01,580
So we're going to elect whatever
president we want.

622
00:27:01,580 --> 00:27:03,700
And older people go vote a lot
more than younger people.

623
00:27:03,700 --> 00:27:04,440
You can change that.

624
00:27:04,440 --> 00:27:06,730
But that's how it is.

625
00:27:06,730 --> 00:27:10,310
So let's talk about
adult development.

626
00:27:10,310 --> 00:27:13,090
I can tell you that if you
compare adult development,

627
00:27:13,090 --> 00:27:15,600
very little is understood
from 20 to 80.

628
00:27:15,600 --> 00:27:17,970
Almost all the research is
taking something like college

629
00:27:17,970 --> 00:27:20,270
students, and something
like 80-year-olds,

630
00:27:20,270 --> 00:27:21,030
and comparing them.

631
00:27:21,030 --> 00:27:24,810
So pretty much minimal
information is available about

632
00:27:24,810 --> 00:27:26,190
everything between 20 and 80.

633
00:27:26,190 --> 00:27:28,430
But we'll look at what we can.

634
00:27:28,430 --> 00:27:30,430
And one of the things we'll talk
about for a moment is the

635
00:27:30,430 --> 00:27:32,220
two kinds of studies we could
look at for development.

636
00:27:32,220 --> 00:27:33,120
This could be about infants.

637
00:27:33,120 --> 00:27:35,780
But we're going to talk
about adults.

638
00:27:35,780 --> 00:27:37,810
Cross-sectional versus
longitudinal, so

639
00:27:37,810 --> 00:27:40,620
cross-sectional is I look
at you as 20-year-olds.

640
00:27:40,620 --> 00:27:42,925
I look at some 80-year-olds in
the Boston community and

641
00:27:42,925 --> 00:27:44,760
compare them.

642
00:27:44,760 --> 00:27:47,340
That's very different than
looking at you at 20 and

643
00:27:47,340 --> 00:27:49,260
seeing you at 80.

644
00:27:49,260 --> 00:27:50,790
Because that's much
more controlled.

645
00:27:50,790 --> 00:27:53,310
That's you with everything
that's special and particular

646
00:27:53,310 --> 00:27:55,960
about you at 20 and 80.

647
00:27:55,960 --> 00:27:58,230
When you go get people who are
20-year-olds from one place

648
00:27:58,230 --> 00:28:02,100
and 80-year-olds from another,
a cross-sectional , study,

649
00:28:02,100 --> 00:28:05,840
that's going to have all
the differences that

650
00:28:05,840 --> 00:28:07,850
go with those cohorts.

651
00:28:07,850 --> 00:28:11,160
So what do we see in these
kinds of things?

652
00:28:14,700 --> 00:28:16,300
So here's some measures.

653
00:28:16,300 --> 00:28:17,340
You've seen this kind
of stuff before.

654
00:28:17,340 --> 00:28:19,085
For things like working memory,
speed of processing,

655
00:28:19,085 --> 00:28:20,380
and long-term memory.

656
00:28:20,380 --> 00:28:22,570
Here's people in their '20s,
people in their '80s, a ski

657
00:28:22,570 --> 00:28:26,250
scope of decline.

658
00:28:26,250 --> 00:28:28,420
Here's things like knowledge
of vocabulary.

659
00:28:28,420 --> 00:28:31,000
And that stays more steady,
so the crystallized fluid

660
00:28:31,000 --> 00:28:33,390
distinction you've already
heard about before.

661
00:28:33,390 --> 00:28:36,470
So what are the strengths and
limitations of cross-sectional

662
00:28:36,470 --> 00:28:38,560
versus longitudinal studies.

663
00:28:38,560 --> 00:28:41,200
So for cross-sectional studies,
they're fast.

664
00:28:41,200 --> 00:28:43,760
If you're a scientist like a
graduate student who has to do

665
00:28:43,760 --> 00:28:47,500
a Ph.D. thesis in a mere six or
seven years, you can go to

666
00:28:47,500 --> 00:28:49,530
experiment with 20-year-olds
and 80-year-olds and have a

667
00:28:49,530 --> 00:28:50,640
conclusion.

668
00:28:50,640 --> 00:28:52,930
If you're a graduate student
who would have to test this

669
00:28:52,930 --> 00:28:56,960
class of 20 and come back to you
in 60 years from now and

670
00:28:56,960 --> 00:29:00,540
see how you're doing, that's
going to be slow progress.

671
00:29:00,540 --> 00:29:03,970
So that's why an overwhelming
amount of evidence is

672
00:29:03,970 --> 00:29:05,970
cross-sectional.

673
00:29:05,970 --> 00:29:07,810
The problem with it
is cohort effects.

674
00:29:07,810 --> 00:29:10,940
We discussed, for example, that
IQ scores go up year by

675
00:29:10,940 --> 00:29:13,200
year throughout the world.

676
00:29:13,200 --> 00:29:15,290
So you're not really comparing
equal things in terms of

677
00:29:15,290 --> 00:29:18,590
educational opportunities,
nutrition, exposure to

678
00:29:18,590 --> 00:29:19,780
information on the internet.

679
00:29:19,780 --> 00:29:22,240
A 20-year-old and an 80-year-old
have lived through

680
00:29:22,240 --> 00:29:24,390
different worlds.

681
00:29:24,390 --> 00:29:26,670
So it's all mixed up in
the measurements.

682
00:29:26,670 --> 00:29:28,480
Not just age, it's different
worlds that

683
00:29:28,480 --> 00:29:30,660
people have lived in.

684
00:29:30,660 --> 00:29:33,060
Longitudinal studies
are painfully slow.

685
00:29:33,060 --> 00:29:34,920
They're more accurate, because
you're looking at change

686
00:29:34,920 --> 00:29:35,570
within a person.

687
00:29:35,570 --> 00:29:38,570
You're holding all the world
things constant.

688
00:29:38,570 --> 00:29:39,930
You have one other weird
thing, which is you get

689
00:29:39,930 --> 00:29:40,910
practice effects.

690
00:29:40,910 --> 00:29:43,700
If you test somebody in the same
test, if you're 60 years

691
00:29:43,700 --> 00:29:44,540
apart, you don't get much.

692
00:29:44,540 --> 00:29:46,570
But if it's maybe three or four
years apart, you take a

693
00:29:46,570 --> 00:29:48,080
test twice, you get
better at it.

694
00:29:48,080 --> 00:29:49,980
So that's a problem with
longitudinal affects when you

695
00:29:49,980 --> 00:29:51,310
retest somebody.

696
00:29:51,310 --> 00:29:53,530
So there's been a few studies
that have looked at relatively

697
00:29:53,530 --> 00:29:56,620
short-term longitudinal and
cross-sectional data.

698
00:29:56,620 --> 00:30:00,840
And here's a ski slope on
the values of fluid

699
00:30:00,840 --> 00:30:02,110
intelligence things.

700
00:30:02,110 --> 00:30:06,260
And it's just made a bit milder
by a longitudinal

701
00:30:06,260 --> 00:30:07,840
design, but not dramatically
different.

702
00:30:07,840 --> 00:30:10,500
So it's not the case of
longitudinal studies.

703
00:30:10,500 --> 00:30:12,550
People used to think oh, these
longitudinal studies are

704
00:30:12,550 --> 00:30:13,530
overestimating that.

705
00:30:13,530 --> 00:30:15,420
Especially if you're older,
you like that thought.

706
00:30:15,420 --> 00:30:17,100
It's a messed up
study approach.

707
00:30:17,100 --> 00:30:19,130
But unfortunately,
cross-sectional ones just

708
00:30:19,130 --> 00:30:22,170
diminish the difference
a little bit.

709
00:30:22,170 --> 00:30:25,170
So people have said,
though, there's

710
00:30:25,170 --> 00:30:26,120
an interesting trade-off.

711
00:30:26,120 --> 00:30:27,860
What's the trade-off, then--

712
00:30:27,860 --> 00:30:29,490
I'll ask you for a moment--

713
00:30:29,490 --> 00:30:33,040
between most of you
are like 18 to 22.

714
00:30:33,040 --> 00:30:36,340
I'll bracket it 17 to 25.

715
00:30:36,340 --> 00:30:38,220
Is that fair?

716
00:30:38,220 --> 00:30:42,250
What advantage do you have
versus somebody in their

717
00:30:42,250 --> 00:30:44,980
mid-'50s like me?

718
00:30:44,980 --> 00:30:51,120
And what disadvantage do you
have in some global sense?

719
00:30:51,120 --> 00:30:51,770
Oh.

720
00:30:51,770 --> 00:30:54,110
That was painful.

721
00:30:54,110 --> 00:30:56,750
The answer was you guys
are physically able.

722
00:30:56,750 --> 00:30:57,190
All right.

723
00:30:57,190 --> 00:30:58,590
That would be true.

724
00:30:58,590 --> 00:31:00,340
There's not many Olympian
sprinters who

725
00:31:00,340 --> 00:31:01,590
are in their mid-'50s.

726
00:31:03,570 --> 00:31:05,110
How about in terms of
cognitive things?

727
00:31:08,650 --> 00:31:12,500
So we just said, for speed
of mental processing,

728
00:31:12,500 --> 00:31:14,470
it's good to be 20.

729
00:31:14,470 --> 00:31:17,650
And then 30-year-olds
are a little slower.

730
00:31:17,650 --> 00:31:18,720
40-year-olds, a little slower.

731
00:31:18,720 --> 00:31:22,540
50, 60, 70, every decade a
little bit slower for speed of

732
00:31:22,540 --> 00:31:23,960
mental processing.

733
00:31:23,960 --> 00:31:25,800
But there's one thing
that's an advantage

734
00:31:25,800 --> 00:31:27,900
with time for cognition.

735
00:31:27,900 --> 00:31:29,066
What's the advantage?

736
00:31:29,066 --> 00:31:30,404
AUDIENCE: [INAUDIBLE].

737
00:31:30,404 --> 00:31:30,850
PROFESSOR: Sorry?

738
00:31:30,850 --> 00:31:31,836
AUDIENCE: Experience.

739
00:31:31,836 --> 00:31:32,960
PROFESSOR: Experience.

740
00:31:32,960 --> 00:31:33,320
Thank you.

741
00:31:33,320 --> 00:31:34,770
Oh yes.

742
00:31:34,770 --> 00:31:36,140
Yes.

743
00:31:36,140 --> 00:31:39,650
Over time, you learn stuff,
especially stuff that you're

744
00:31:39,650 --> 00:31:40,630
exposed to a lot.

745
00:31:40,630 --> 00:31:44,120
So time is a trade-off
within adulthood.

746
00:31:44,120 --> 00:31:46,700
You lose some speeded
capacities.

747
00:31:46,700 --> 00:31:49,800
You gain some specific knowledge
or experience.

748
00:31:49,800 --> 00:31:51,830
So they looked at studies
like these, air traffic

749
00:31:51,830 --> 00:31:53,420
controllers in Canada.

750
00:31:53,420 --> 00:31:57,350
And this is very relevant.

751
00:31:57,350 --> 00:32:00,360
Especially now, air traffic
controllers are in the news

752
00:32:00,360 --> 00:32:02,420
more than they want to be.

753
00:32:02,420 --> 00:32:02,790
You've seen them?

754
00:32:02,790 --> 00:32:04,030
Unfortunately, they're
napping.

755
00:32:04,030 --> 00:32:05,390
They're playing movies,
some of them.

756
00:32:05,390 --> 00:32:06,770
I'm sure it's a tiny minority.

757
00:32:06,770 --> 00:32:10,760
But it's worrisome if you're a
member of the flying public.

758
00:32:10,760 --> 00:32:11,620
So here's another question.

759
00:32:11,620 --> 00:32:13,880
At what age should you tell
somebody, well, I think we

760
00:32:13,880 --> 00:32:15,980
don't need you to be an air
controller anymore, because

761
00:32:15,980 --> 00:32:19,680
you're not with it enough
for us to feel safe.

762
00:32:19,680 --> 00:32:21,470
So people are probing
this all the time.

763
00:32:24,150 --> 00:32:27,920
The average retirement age in
the US is 55, in Canada, 65.

764
00:32:27,920 --> 00:32:29,860
Is one more correct
than the other?

765
00:32:29,860 --> 00:32:31,870
And so here's what they found
when they looked at air

766
00:32:31,870 --> 00:32:33,680
traffic controllers.

767
00:32:33,680 --> 00:32:35,950
Age influences processing
speed but not task

768
00:32:35,950 --> 00:32:37,130
performance.

769
00:32:37,130 --> 00:32:39,470
So what we're thinking is older
people aren't better.

770
00:32:39,470 --> 00:32:40,130
But they're not worse.

771
00:32:40,130 --> 00:32:42,880
Maybe there's a trade-off
between speed and experience.

772
00:32:42,880 --> 00:32:45,930
And it kind of evens out until
some age where it will no

773
00:32:45,930 --> 00:32:47,410
longer even out.

774
00:32:47,410 --> 00:32:51,420
118 pilots, 40 to 69, they
took place in flight

775
00:32:51,420 --> 00:32:53,530
simulators and tested three
times across three years.

776
00:32:53,530 --> 00:32:55,910
It's a longitudinal design
and a flight simulator.

777
00:32:55,910 --> 00:32:59,720
The older pilots were worse the
first time they did it.

778
00:32:59,720 --> 00:33:01,150
Now some time is passing.

779
00:33:01,150 --> 00:33:02,910
But then they outperformed
the younger pilots in

780
00:33:02,910 --> 00:33:04,350
years two and three.

781
00:33:04,350 --> 00:33:06,310
That is, once they had some
experience with the new

782
00:33:06,310 --> 00:33:09,000
situation, they could apply,
presumably, their prior

783
00:33:09,000 --> 00:33:10,510
experience.

784
00:33:10,510 --> 00:33:12,520
But the very first time they did
it when they have to use

785
00:33:12,520 --> 00:33:14,320
their fluid intelligence to
figure out what's going on,

786
00:33:14,320 --> 00:33:15,250
they were worse.

787
00:33:15,250 --> 00:33:19,200
So you can see some trade-offs
between raw processing, speed,

788
00:33:19,200 --> 00:33:22,700
and flexibility that goes with
the young adulthood and some

789
00:33:22,700 --> 00:33:23,970
degree of knowledge
and expertise

790
00:33:23,970 --> 00:33:24,990
that's gained over time.

791
00:33:24,990 --> 00:33:28,180
There's trade-offs
on these things.

792
00:33:28,180 --> 00:33:30,180
How about in memory, declarative
memory that we

793
00:33:30,180 --> 00:33:31,910
talked about, every
day memory.

794
00:33:31,910 --> 00:33:32,570
I'll show you in a moment.

795
00:33:32,570 --> 00:33:35,720
There's mild, steady decline
in healthy aging severe in

796
00:33:35,720 --> 00:33:36,900
Alzheimer's.

797
00:33:36,900 --> 00:33:38,670
Implicit memory, we
talked about that.

798
00:33:38,670 --> 00:33:40,690
It can be more steady
across ages.

799
00:33:40,690 --> 00:33:44,340
But let me focus on explicit
memory, declarative memory.

800
00:33:44,340 --> 00:33:46,990
We're going to figure out why
the projector is washing these

801
00:33:46,990 --> 00:33:47,710
things out so much.

802
00:33:47,710 --> 00:33:49,850
But here's a slide that
you don't have to see

803
00:33:49,850 --> 00:33:51,010
very much to know.

804
00:33:51,010 --> 00:33:54,650
Long-term memory performance
is going down quite sharply

805
00:33:54,650 --> 00:33:57,640
year by year as you get older.

806
00:33:57,640 --> 00:33:59,970
But here's something that was
a huge surprise from brain

807
00:33:59,970 --> 00:34:01,200
imaging, a huge surprise.

808
00:34:01,200 --> 00:34:02,940
And the thing that if you didn't
have brain imaging, you

809
00:34:02,940 --> 00:34:05,650
wouldn't even conceive that
it could have existed.

810
00:34:05,650 --> 00:34:08,310
So many studies have done
brain imaging as people

811
00:34:08,310 --> 00:34:10,960
perform various kinds of tasks,
memory tasks in this

812
00:34:10,960 --> 00:34:13,580
case, with young adults
and older adults.

813
00:34:13,580 --> 00:34:13,710
And

814
00:34:13,710 --> 00:34:17,500
what they found, unexpectedly,
was this.

815
00:34:17,500 --> 00:34:22,710
Young adults would typically
activate one side of the

816
00:34:22,710 --> 00:34:25,090
prefrontal cortex typically in
regards to whether it was

817
00:34:25,090 --> 00:34:26,380
verbal or spatial.

818
00:34:26,380 --> 00:34:29,460
So here's young adults mostly
on one side, mostly on one

819
00:34:29,460 --> 00:34:34,580
side, mostly on one side,
mostly on one side.

820
00:34:34,580 --> 00:34:37,940
Healthy older adults in good
health characteristically

821
00:34:37,940 --> 00:34:41,630
turned on both sides of the
brain as they were performing

822
00:34:41,630 --> 00:34:44,150
these memory tasks.

823
00:34:44,150 --> 00:34:45,870
So you wouldn't have known
that if you didn't have

824
00:34:45,870 --> 00:34:49,260
imaging, because who could
have thought about that?

825
00:34:49,260 --> 00:34:52,620
So then there was a little bit
of a debate in the field with

826
00:34:52,620 --> 00:34:55,679
the fact that adults were
turning on both sides of their

827
00:34:55,679 --> 00:34:58,200
hemispheres whereas adults
were just picking one

828
00:34:58,200 --> 00:34:59,220
or just using one.

829
00:34:59,220 --> 00:35:01,450
Was that a good thing
or a bad thing?

830
00:35:01,450 --> 00:35:03,960
So people said, well,
it's a bad thing.

831
00:35:03,960 --> 00:35:05,860
Because maybe as you get
older, you lose your

832
00:35:05,860 --> 00:35:09,550
specializations, and you're
using the wrong stuff.

833
00:35:09,550 --> 00:35:10,820
It's as if I need
my physics book.

834
00:35:10,820 --> 00:35:12,600
And I'm going to grab
my chemistry book.

835
00:35:12,600 --> 00:35:14,930
Well, just grab your
physics book.

836
00:35:14,930 --> 00:35:16,330
Just grab the right thing.

837
00:35:16,330 --> 00:35:18,770
Why are you getting other stuff
that's not relevant that

838
00:35:18,770 --> 00:35:20,440
could mess you up and
slow you down?

839
00:35:20,440 --> 00:35:22,360
So some people said, you're
sort of losing the

840
00:35:22,360 --> 00:35:24,460
specializations of peak
young adulthood.

841
00:35:24,460 --> 00:35:28,110
You're leaking brain activity
in the wrong places.

842
00:35:28,110 --> 00:35:31,070
It's yet another sad sign
of getting older.

843
00:35:31,070 --> 00:35:32,390
Here's an alternative one.

844
00:35:32,390 --> 00:35:33,100
Well, you get older.

845
00:35:33,100 --> 00:35:35,220
But maybe you get some
compensatory mechanisms.

846
00:35:35,220 --> 00:35:38,070
You realize at some level in
your brain that you can't do

847
00:35:38,070 --> 00:35:39,900
what you could when
you were 20.

848
00:35:39,900 --> 00:35:43,040
And you make up for that by
somehow using two sides of

849
00:35:43,040 --> 00:35:44,790
your brain instead of one.

850
00:35:44,790 --> 00:35:46,300
So that would be a good thing.

851
00:35:46,300 --> 00:35:49,690
So how would you decide that?

852
00:35:49,690 --> 00:35:52,270
How would you decide whether
using the two sides of your

853
00:35:52,270 --> 00:35:56,400
brain when you're an older adult
is a helpful thing, part

854
00:35:56,400 --> 00:35:59,920
of the solution to keeping your
cognition going, or is it

855
00:35:59,920 --> 00:36:03,720
part of the problem of losing
long-term memory abilities as

856
00:36:03,720 --> 00:36:04,790
you get older while
they're declining.

857
00:36:04,790 --> 00:36:06,640
How would you decide that?

858
00:36:06,640 --> 00:36:08,540
There's kind of an
easy answer.

859
00:36:08,540 --> 00:36:08,980
AUDIENCE: [INAUDIBLE].

860
00:36:08,980 --> 00:36:09,820
PROFESSOR: Sorry.

861
00:36:09,820 --> 00:36:11,380
AUDIENCE: [INAUDIBLE].

862
00:36:11,380 --> 00:36:12,250
PROFESSOR: You what?

863
00:36:12,250 --> 00:36:14,300
AUDIENCE: Like, split
their brains.

864
00:36:14,300 --> 00:36:16,670
PROFESSOR: Yes.

865
00:36:16,670 --> 00:36:18,490
It's a suggestion we should take
older people, split their

866
00:36:18,490 --> 00:36:21,620
brains, and see how
they're doing.

867
00:36:21,620 --> 00:36:24,300
Well, older people,
their long-term

868
00:36:24,300 --> 00:36:26,090
memory is not that bad.

869
00:36:26,090 --> 00:36:27,610
So here was the approach.

870
00:36:27,610 --> 00:36:28,470
It seems reasonable.

871
00:36:28,470 --> 00:36:31,000
They say amongst older people,
some people do better and

872
00:36:31,000 --> 00:36:33,240
worse in terms of the memory.

873
00:36:33,240 --> 00:36:37,070
Does better memory go with using
two sides or one side?

874
00:36:37,070 --> 00:36:39,660
And what was found, and
here's one example.

875
00:36:39,660 --> 00:36:42,330
Here's young people using one
side of their frontal cortex

876
00:36:42,330 --> 00:36:43,930
as they perform a memory task.

877
00:36:43,930 --> 00:36:46,750
Here's older people whose
memory was not so good.

878
00:36:46,750 --> 00:36:48,510
Here's older people whose
memory was good.

879
00:36:48,510 --> 00:36:50,450
And here's a similar finding.

880
00:36:50,450 --> 00:36:54,620
So the suggestion was that older
people who used both

881
00:36:54,620 --> 00:36:56,930
frontal cortices were actually
doing better.

882
00:36:56,930 --> 00:36:59,750
They were having less of an
effective age on cognition.

883
00:36:59,750 --> 00:37:02,710
So the answer seems to be,
it's a good thing.

884
00:37:02,710 --> 00:37:05,120
And if you're older, you somehow
compensate for some of

885
00:37:05,120 --> 00:37:09,030
the decrease in long-term
ability by applying more

886
00:37:09,030 --> 00:37:10,690
neural systems to support
your performance.

887
00:37:16,170 --> 00:37:17,580
Older adults are really
interested in this.

888
00:37:17,580 --> 00:37:18,190
You are not.

889
00:37:18,190 --> 00:37:20,270
In about 30 years,
you might be.

890
00:37:20,270 --> 00:37:22,410
But older adults are really
interested in what can I do to

891
00:37:22,410 --> 00:37:23,340
keep myself going?

892
00:37:23,340 --> 00:37:27,650
Because I'm going to live to be
80, 90, or 100 with just a

893
00:37:27,650 --> 00:37:28,970
little bit of luck.

894
00:37:28,970 --> 00:37:32,160
How can I keep my quality
of life high in terms of

895
00:37:32,160 --> 00:37:34,220
cognition and mental
abilities?

896
00:37:34,220 --> 00:37:37,160
So one thing that people have
found is that, on average,

897
00:37:37,160 --> 00:37:41,320
higher education is correlated
with-- and there's many

898
00:37:41,320 --> 00:37:42,950
interpretations of this--

899
00:37:42,950 --> 00:37:45,750
better cognitive abilities and
less likelihood of getting

900
00:37:45,750 --> 00:37:47,450
Alzheimer's, or getting
Alzheimer's, if you're going

901
00:37:47,450 --> 00:37:50,860
to get it, at an older age.

902
00:37:50,860 --> 00:37:52,940
So that's kind of interesting.

903
00:37:52,940 --> 00:37:54,150
It's good to go to college.

904
00:37:54,150 --> 00:37:55,910
It's good to keep being educated
in some sense.

905
00:37:55,910 --> 00:37:57,340
It doesn't have to be formal.

906
00:37:57,340 --> 00:38:00,450
But formal education correlates
with that.

907
00:38:00,450 --> 00:38:01,480
Now here was a surprise.

908
00:38:01,480 --> 00:38:02,360
And now you tell
me what it is.

909
00:38:02,360 --> 00:38:03,990
So how would that work?

910
00:38:03,990 --> 00:38:05,860
How would sitting there and
listening to me really

911
00:38:05,860 --> 00:38:09,850
carefully right now give you an
extra decade of cognitive

912
00:38:09,850 --> 00:38:12,581
ability when you're 80?

913
00:38:12,581 --> 00:38:14,500
All right, now I've got
your attention.

914
00:38:14,500 --> 00:38:16,470
How would that work
biologically?

915
00:38:16,470 --> 00:38:18,850
Is education kind of going in
your brain and saying, we're

916
00:38:18,850 --> 00:38:19,720
knocking all these things in.

917
00:38:19,720 --> 00:38:20,490
And we're keeping them here.

918
00:38:20,490 --> 00:38:22,230
And we're not going to let
you have any injury when

919
00:38:22,230 --> 00:38:23,000
you're 40 or 50.

920
00:38:23,000 --> 00:38:24,560
How does that work?

921
00:38:24,560 --> 00:38:26,480
So I'm going to tell you one
more piece of information,

922
00:38:26,480 --> 00:38:26,950
which is this.

923
00:38:26,950 --> 00:38:28,930
And you tell me what
you think.

924
00:38:28,930 --> 00:38:31,680
So the other thing that we know
is there's evidence that

925
00:38:31,680 --> 00:38:37,020
once you get the diagnosis of
Alzheimer's disease, then the

926
00:38:37,020 --> 00:38:39,385
more educated you are, the
faster you decline.

927
00:38:44,690 --> 00:38:46,430
And I don't think the story
is all done yet.

928
00:38:46,430 --> 00:38:47,730
Because people are
complicated.

929
00:38:47,730 --> 00:38:49,470
But this is the current
evidence.

930
00:38:49,470 --> 00:38:52,580
So how do you interpret that?

931
00:38:52,580 --> 00:38:53,700
So here's the interpretation.

932
00:38:53,700 --> 00:38:56,650
The interpretation is more
education gives you more

933
00:38:56,650 --> 00:38:59,190
mental tools, what people will
call cognitive reserve.

934
00:38:59,190 --> 00:39:01,840
You have more things going for
you like maybe the ability to

935
00:39:01,840 --> 00:39:04,310
use two hemispheres.

936
00:39:04,310 --> 00:39:08,110
That will protect you as
something like some brain

937
00:39:08,110 --> 00:39:10,780
injury happens over time, like
an Alzheimer's disease, or

938
00:39:10,780 --> 00:39:13,770
other causes of slowed
or diminished

939
00:39:13,770 --> 00:39:14,770
cognition in old age.

940
00:39:14,770 --> 00:39:15,600
That will help you.

941
00:39:15,600 --> 00:39:18,170
You have more tools with
which to keep operating

942
00:39:18,170 --> 00:39:19,770
successfully.

943
00:39:19,770 --> 00:39:22,340
But once Alzheimer's disease
become severe enough in the

944
00:39:22,340 --> 00:39:25,070
brain that those tools are no
longer available to you, then

945
00:39:25,070 --> 00:39:27,680
the more educated you are,
the more you plummet.

946
00:39:27,680 --> 00:39:30,680
Because everything's done.

947
00:39:30,680 --> 00:39:32,250
So we now know something--
and I'll just say

948
00:39:32,250 --> 00:39:32,680
a word about this--

949
00:39:32,680 --> 00:39:34,630
Alzheimer's disease-- and
this is compelling

950
00:39:34,630 --> 00:39:35,530
evidence for this--

951
00:39:35,530 --> 00:39:40,540
starts in your brain
about 15 years

952
00:39:40,540 --> 00:39:42,550
before you get the diagnosis.

953
00:39:42,550 --> 00:39:44,840
And it could be more
than that.

954
00:39:44,840 --> 00:39:47,690
That's how far we can track
it back by brain imaging.

955
00:39:47,690 --> 00:39:51,830
So if an adult is diagnosed
with Alzheimer's at 70,

956
00:39:51,830 --> 00:39:57,330
somewhere around 55, something
has started that will

957
00:39:57,330 --> 00:40:00,960
ultimately be injury enough
to lead to dementia and

958
00:40:00,960 --> 00:40:02,610
Alzheimer's disease.

959
00:40:02,610 --> 00:40:05,520
And that's why there's such
a big emphasis on early

960
00:40:05,520 --> 00:40:06,850
identification.

961
00:40:06,850 --> 00:40:08,540
Because it's very hard to
treat a brain that's

962
00:40:08,540 --> 00:40:10,090
had a lot of injury.

963
00:40:10,090 --> 00:40:12,580
You want to catch the
people at 55 or 60.

964
00:40:12,580 --> 00:40:15,540
So we also know that lifelong
cognitively is good.

965
00:40:15,540 --> 00:40:17,490
Conscientious, we talked
about that.

966
00:40:17,490 --> 00:40:19,155
And here, again,
comes exercise.

967
00:40:22,630 --> 00:40:23,730
So they took a study.

968
00:40:23,730 --> 00:40:25,470
This is now a random assignment
study, finally a

969
00:40:25,470 --> 00:40:29,760
full on experiment, where they
took sedentary people, people

970
00:40:29,760 --> 00:40:31,880
who were not exercising over 60,
and assigned them to two

971
00:40:31,880 --> 00:40:35,390
groups, an aerobic training
group who did walking and

972
00:40:35,390 --> 00:40:37,085
swimming, so some really
exercise, and non-aerobic

973
00:40:37,085 --> 00:40:39,090
group who did toning
and stretching.

974
00:40:39,090 --> 00:40:40,750
So they thought they
were special.

975
00:40:40,750 --> 00:40:41,600
They were active.

976
00:40:41,600 --> 00:40:44,040
But they weren't doing
the aerobic exercise.

977
00:40:44,040 --> 00:40:46,640
And they didn't do it a
phenomenal amount of time, an

978
00:40:46,640 --> 00:40:48,300
hour a day, a few times
a week for months.

979
00:40:48,300 --> 00:40:51,400
It's not a brutal exercise
schedule.

980
00:40:51,400 --> 00:40:52,570
What happens?

981
00:40:52,570 --> 00:40:54,250
It's kind of amazing
what happened.

982
00:40:54,250 --> 00:40:56,760
These are healthy people
but not very active.

983
00:40:56,760 --> 00:40:59,620
What's shown here in the red
bars are the cognitive

984
00:40:59,620 --> 00:41:02,500
performances after the
exercise of the

985
00:41:02,500 --> 00:41:03,260
healthy older people.

986
00:41:03,260 --> 00:41:05,980
And blue bars are the people
who did the stretching and

987
00:41:05,980 --> 00:41:07,540
toning, not the aerobic
exercise.

988
00:41:07,540 --> 00:41:10,730
So very substantial gains in
cognitive abilities from a few

989
00:41:10,730 --> 00:41:13,220
months of moderate exercise.

990
00:41:13,220 --> 00:41:17,620
And in the brain, both by
functional MRI and by

991
00:41:17,620 --> 00:41:21,410
structural MRI, in gray matter,
and white matter,

992
00:41:21,410 --> 00:41:24,320
physically measurable changes
in the brain for the group

993
00:41:24,320 --> 00:41:28,740
that did the aerobic exercise
a couple times a week for a

994
00:41:28,740 --> 00:41:30,760
few months compared to
the group that did

995
00:41:30,760 --> 00:41:34,000
the less active exercises.

996
00:41:34,000 --> 00:41:34,730
That's amazing.

997
00:41:34,730 --> 00:41:36,390
The brain changes.

998
00:41:36,390 --> 00:41:38,300
Cognition changes.

999
00:41:38,300 --> 00:41:40,720
Again, no pill you can pop.

1000
00:41:40,720 --> 00:41:43,790
And you're making new neurons in
your dentate gyrus to boot.

1001
00:41:43,790 --> 00:41:46,530
So all of us want
the easy out.

1002
00:41:46,530 --> 00:41:49,740
But exercise is the most
compelling story for keeping

1003
00:41:49,740 --> 00:41:53,060
your brain optimized
that we know.

1004
00:41:53,060 --> 00:41:54,150
Now here's a remarkable thing.

1005
00:41:54,150 --> 00:41:56,110
Exercise, we kind of get.

1006
00:41:56,110 --> 00:41:58,290
Actually, if you think about
it, we don't know the

1007
00:41:58,290 --> 00:42:00,260
mechanism at all.

1008
00:42:00,260 --> 00:42:02,080
I mean, you're running
around like this.

1009
00:42:02,080 --> 00:42:04,530
Now how is that pushing up your
neurons in your brain?

1010
00:42:04,530 --> 00:42:06,770
But here's something
very psychological

1011
00:42:06,770 --> 00:42:07,990
that's kind of stunning.

1012
00:42:07,990 --> 00:42:09,770
And at first, I almost didn't
believe it when I read it.

1013
00:42:09,770 --> 00:42:10,825
But there's been a few
other studies that

1014
00:42:10,825 --> 00:42:12,180
have supported this.

1015
00:42:12,180 --> 00:42:14,950
We often think, well, exercise
is something real.

1016
00:42:14,950 --> 00:42:17,590
Attitudes, even in a psychology
course, attitudes,

1017
00:42:17,590 --> 00:42:19,160
they're just attitudes.

1018
00:42:19,160 --> 00:42:20,180
So look at this.

1019
00:42:20,180 --> 00:42:21,930
And then you can think
about this.

1020
00:42:21,930 --> 00:42:25,750
So they looked in a longitudinal
study of over 400

1021
00:42:25,750 --> 00:42:27,480
in the Baltimore Longitudinal
Study of Aging.

1022
00:42:27,480 --> 00:42:28,360
They started under 50.

1023
00:42:28,360 --> 00:42:29,930
But they kept going with them.

1024
00:42:29,930 --> 00:42:32,900
They gave them a questionnaire
on attitudes about aging.

1025
00:42:32,900 --> 00:42:34,740
So they said, are older people,
for example, more

1026
00:42:34,740 --> 00:42:36,470
absent-minded or less
intelligent?

1027
00:42:36,470 --> 00:42:38,470
And some people say,
oh my gosh.

1028
00:42:38,470 --> 00:42:40,040
Older people are very
absent-minded.

1029
00:42:40,040 --> 00:42:41,710
They're very less intelligent.

1030
00:42:41,710 --> 00:42:43,170
Other people think it's
just a milder think.

1031
00:42:43,170 --> 00:42:45,980
People vary in their estimates
of how severe these changes

1032
00:42:45,980 --> 00:42:47,810
are in old age.

1033
00:42:47,810 --> 00:42:50,250
Then they measured something
very concrete and real, the

1034
00:42:50,250 --> 00:42:54,210
number of cardiovascular events,
like stroke or heart

1035
00:42:54,210 --> 00:42:58,050
attack, over the
next 38 years.

1036
00:42:58,050 --> 00:42:59,710
So this is a real physical
measurement.

1037
00:42:59,710 --> 00:43:00,980
This isn't an attitude.

1038
00:43:00,980 --> 00:43:03,170
How powerful is an attitude?

1039
00:43:03,170 --> 00:43:05,590
Well, it's kind of stunning,
unbelievably

1040
00:43:05,590 --> 00:43:07,490
powerful in some ways.

1041
00:43:07,490 --> 00:43:08,710
We don't know if it's the
attitude or something

1042
00:43:08,710 --> 00:43:09,680
correlated.

1043
00:43:09,680 --> 00:43:13,600
But here's the percent with
strokes or heart attacks.

1044
00:43:13,600 --> 00:43:18,270
Here's the people who had
negative age stereotypes.

1045
00:43:18,270 --> 00:43:21,890
And here's the people who had
positive age stereotypes.

1046
00:43:21,890 --> 00:43:23,460
So one always has to be
worried about the

1047
00:43:23,460 --> 00:43:25,060
chicken and egg issue.

1048
00:43:25,060 --> 00:43:26,840
Maybe if you had a lot of
strokes and heart attacks,

1049
00:43:26,840 --> 00:43:28,980
you're not so optimistic
about your old age.

1050
00:43:28,980 --> 00:43:31,300
But they were measuring these
things at the beginning, they

1051
00:43:31,300 --> 00:43:32,170
were very similar.

1052
00:43:32,170 --> 00:43:33,300
So they weren't starting
out with

1053
00:43:33,300 --> 00:43:34,600
different health problems.

1054
00:43:34,600 --> 00:43:38,180
So something about attitudes
seems to chip in to the most

1055
00:43:38,180 --> 00:43:40,120
core aspects of physical
health.

1056
00:43:40,120 --> 00:43:42,020
But none of us understand
the mechanism.

1057
00:43:42,020 --> 00:43:42,360
Yes?

1058
00:43:42,360 --> 00:43:43,993
AUDIENCE: Wouldn't family
history have a

1059
00:43:43,993 --> 00:43:45,610
lot to do with that?

1060
00:43:45,610 --> 00:43:46,970
PROFESSOR: So the question is
how about family history?

1061
00:43:46,970 --> 00:43:48,180
It could be mixed into that.

1062
00:43:48,180 --> 00:43:48,930
AUDIENCE: [INTERPOSING VOICES].

1063
00:43:48,930 --> 00:43:49,780
PROFESSOR: Yeah.

1064
00:43:49,780 --> 00:43:51,901
That's a very good.

1065
00:43:51,901 --> 00:43:54,400
Then it's not just
attitudes, right?

1066
00:43:54,400 --> 00:43:55,810
Or it could be not
attitudes it all.

1067
00:43:59,040 --> 00:44:01,020
And here's the concept.

1068
00:44:01,020 --> 00:44:03,980
That regardless of your age--
but age is one of the most

1069
00:44:03,980 --> 00:44:06,390
powerful pieces of the story--

1070
00:44:06,390 --> 00:44:09,790
when your time is limited,
people focus on social goals

1071
00:44:09,790 --> 00:44:13,130
related to emotional meaning and
emotional satisfaction and

1072
00:44:13,130 --> 00:44:15,150
less related to knowledge
acquisition.

1073
00:44:15,150 --> 00:44:19,850
That depending on the moment of
your life on average, when

1074
00:44:19,850 --> 00:44:22,060
you're in adolescence, and
you're in college and graduate

1075
00:44:22,060 --> 00:44:24,730
school, and you're beginning
your residency, or becoming a

1076
00:44:24,730 --> 00:44:27,990
junior partner at a law firm,
you're at an age of huge

1077
00:44:27,990 --> 00:44:29,180
information acquisition.

1078
00:44:29,180 --> 00:44:31,860
What you want to know is what
do I need to know to do

1079
00:44:31,860 --> 00:44:33,340
something important,
significant,

1080
00:44:33,340 --> 00:44:35,290
valuable in my life?

1081
00:44:35,290 --> 00:44:37,590
You're sitting here acquiring
knowledge.

1082
00:44:37,590 --> 00:44:40,360
College is four years of
acquiring knowledge in terms

1083
00:44:40,360 --> 00:44:42,260
of classrooms and majors.

1084
00:44:42,260 --> 00:44:43,540
You guys do other things too.

1085
00:44:43,540 --> 00:44:48,360
But the number one mission is
acquire that knowledge.

1086
00:44:48,360 --> 00:44:52,090
Now when you get older, you
don't really want so much

1087
00:44:52,090 --> 00:44:53,010
information anymore.

1088
00:44:53,010 --> 00:44:55,180
And maybe what you're much more
interested in is how you

1089
00:44:55,180 --> 00:44:57,940
regulate your feelings, how
positive can you make your

1090
00:44:57,940 --> 00:45:01,770
life, not by being adventurous,
taking risks, and

1091
00:45:01,770 --> 00:45:03,690
all this kind of stuff,
but by finding

1092
00:45:03,690 --> 00:45:04,810
a way towards happiness.

1093
00:45:04,810 --> 00:45:06,060
And I'm going to show you
a bunch of research that

1094
00:45:06,060 --> 00:45:09,330
suggests that young adulthood
is full about acquisition of

1095
00:45:09,330 --> 00:45:11,910
information through adventure.

1096
00:45:11,910 --> 00:45:16,560
And old age, on average you're
focused to regulate your

1097
00:45:16,560 --> 00:45:18,730
emotions in positive ways.

1098
00:45:18,730 --> 00:45:21,220
And so sometimes people
will call that wisdom.

1099
00:45:21,220 --> 00:45:23,470
Although, you could just say
it's different things for

1100
00:45:23,470 --> 00:45:26,040
different ages are desirable.

1101
00:45:26,040 --> 00:45:28,780
And part of the support came
from the following result,

1102
00:45:28,780 --> 00:45:30,810
which has been found many,
many, many times.

1103
00:45:30,810 --> 00:45:33,290
But it was kind of stunning when
it was first reported.

1104
00:45:33,290 --> 00:45:36,170
So this is where people were
asked, how happy are you?

1105
00:45:36,170 --> 00:45:37,370
Are you satisfied
with your life?

1106
00:45:37,370 --> 00:45:40,700
So here's a younger adults,
18 to 50 basically.

1107
00:45:40,700 --> 00:45:42,430
About half of them said they're
very satisfied.

1108
00:45:42,430 --> 00:45:46,110
But it zooms up if
you're older.

1109
00:45:46,110 --> 00:45:48,390
How many people are satisfied
with their standard of living?

1110
00:45:48,390 --> 00:45:49,500
40 if you're younger.

1111
00:45:49,500 --> 00:45:50,990
60 if you're older.

1112
00:45:50,990 --> 00:45:54,220
Frequency of depression,
for example, never.

1113
00:45:54,220 --> 00:45:56,350
Let's pick often.

1114
00:45:56,350 --> 00:45:58,785
It's higher for younger
people.

1115
00:45:58,785 --> 00:46:01,570
They have more frequent thoughts
about suicide.

1116
00:46:01,570 --> 00:46:05,700
By every measure you can make,
if we give you a questionnaire

1117
00:46:05,700 --> 00:46:08,080
like this, on average, for
20-year-olds or 30-year-olds,

1118
00:46:08,080 --> 00:46:12,500
you would report more
unhappiness than older people,

1119
00:46:12,500 --> 00:46:13,360
on average.

1120
00:46:13,360 --> 00:46:15,560
Of course, it varies.

1121
00:46:15,560 --> 00:46:18,790
But that's kind of a surprise
maybe or not.

1122
00:46:18,790 --> 00:46:20,180
And everybody has found that.

1123
00:46:20,180 --> 00:46:21,040
No, not a surprise?

1124
00:46:21,040 --> 00:46:24,080
AUDIENCE: I mean, just because
they report something, doesn't

1125
00:46:24,080 --> 00:46:26,656
mean that's the way it is.

1126
00:46:26,656 --> 00:46:28,430
PROFESSOR: Ah well we'll come
back to this again.

1127
00:46:28,430 --> 00:46:28,800
Yes.

1128
00:46:28,800 --> 00:46:30,200
Just because you say
you're happier

1129
00:46:30,200 --> 00:46:32,620
doesn't mean you're happier.

1130
00:46:32,620 --> 00:46:35,071
We don't have a better
way than that though.

1131
00:46:35,071 --> 00:46:37,050
We can't say, oh, you
think you're happy.

1132
00:46:37,050 --> 00:46:39,170
But you'd be so happy if
you were at Caltech.

1133
00:46:39,170 --> 00:46:40,420
You'd be just so happy.

1134
00:46:43,970 --> 00:46:45,360
I'm a brain measurer.

1135
00:46:45,360 --> 00:46:47,520
So I like objective measures.

1136
00:46:47,520 --> 00:46:49,160
I think if a person tells
you they're happy,

1137
00:46:49,160 --> 00:46:50,365
they probably are.

1138
00:46:50,365 --> 00:46:51,550
There are certain moments,
I know, when

1139
00:46:51,550 --> 00:46:52,260
people tell you that.

1140
00:46:52,260 --> 00:46:52,770
Well, we'll see.

1141
00:46:52,770 --> 00:46:53,310
Who knows?

1142
00:46:53,310 --> 00:46:53,990
I agree with you.

1143
00:46:53,990 --> 00:46:56,140
It's a concern.

1144
00:46:56,140 --> 00:46:58,460
So here's the thought, that
motivation and goals are set

1145
00:46:58,460 --> 00:46:59,500
by temporal context.

1146
00:46:59,500 --> 00:47:01,700
At times, they're perceived
as limited.

1147
00:47:01,700 --> 00:47:04,160
And all this will come that the
older you get, the more

1148
00:47:04,160 --> 00:47:06,840
you focus on the positive
things in the world.

1149
00:47:06,840 --> 00:47:10,000
And what makes you happy is to
focus on positive things and

1150
00:47:10,000 --> 00:47:11,150
ignore the negative.

1151
00:47:11,150 --> 00:47:14,250
So how true might this
be experimentally?

1152
00:47:14,250 --> 00:47:16,180
So they had students-- ah, this
is really washed out--

1153
00:47:16,180 --> 00:47:19,020
capture these special moments,
this same ad.

1154
00:47:19,020 --> 00:47:24,160
And this one says, "Capture the
special moments." And this

1155
00:47:24,160 --> 00:47:28,630
one says, "Capture the
unexplored world."

1156
00:47:28,630 --> 00:47:30,550
So if you're an information
seeker, which is better? the

1157
00:47:30,550 --> 00:47:32,110
unexplored world or the special

1158
00:47:32,110 --> 00:47:34,680
moments, which is better?

1159
00:47:34,680 --> 00:47:35,580
The unexplored world, right?

1160
00:47:35,580 --> 00:47:36,450
You're a 20-year-old.

1161
00:47:36,450 --> 00:47:38,530
Unexplored Is awesome.

1162
00:47:38,530 --> 00:47:40,590
Young people prefer this ad.

1163
00:47:40,590 --> 00:47:42,490
Older people prefer the
special moments.

1164
00:47:42,490 --> 00:47:45,170
And by special moments, we mean
emotionally satisfying.

1165
00:47:45,170 --> 00:47:45,940
Right?

1166
00:47:45,940 --> 00:47:47,420
OK.

1167
00:47:47,420 --> 00:47:48,410
Here's another one.

1168
00:47:48,410 --> 00:47:51,110
They show you up pictures of
a positive and negative

1169
00:47:51,110 --> 00:47:52,200
expression.

1170
00:47:52,200 --> 00:47:52,760
It flashes away.

1171
00:47:52,760 --> 00:47:54,740
And there's a dot left.

1172
00:47:54,740 --> 00:47:56,410
If the dot appears on the
right, you push your

1173
00:47:56,410 --> 00:47:57,070
right-hand button.

1174
00:47:57,070 --> 00:47:59,160
If the dot appears on
the left, you push

1175
00:47:59,160 --> 00:47:59,930
the left-hand button.

1176
00:47:59,930 --> 00:48:01,460
It's simply pushing to a dot.

1177
00:48:01,460 --> 00:48:03,960
But if the dot is in the place
where you just saw, either a

1178
00:48:03,960 --> 00:48:05,530
negative or a neutral face.

1179
00:48:05,530 --> 00:48:08,110
And what they find is for
younger people, they're about

1180
00:48:08,110 --> 00:48:10,760
as fast whether the dot appears
where the neutral or

1181
00:48:10,760 --> 00:48:11,580
negative face was.

1182
00:48:11,580 --> 00:48:12,810
They don't really care.

1183
00:48:12,810 --> 00:48:15,910
For the older people, they're
much faster if the dot appears

1184
00:48:15,910 --> 00:48:17,980
where the positive face
had just been.

1185
00:48:17,980 --> 00:48:21,550
As if their attention was locked
to the positive face.

1186
00:48:21,550 --> 00:48:22,590
Oh, the dot appears there.

1187
00:48:22,590 --> 00:48:24,170
I'm ready to go.

1188
00:48:24,170 --> 00:48:26,000
Locked on the positive face
if the dot appears here.

1189
00:48:26,000 --> 00:48:26,890
You go, whoa, whoa, whoa.

1190
00:48:26,890 --> 00:48:28,270
You shift your attention.

1191
00:48:28,270 --> 00:48:30,240
And that takes extra time.

1192
00:48:30,240 --> 00:48:33,080
So you're locked to the positive
when you see a

1193
00:48:33,080 --> 00:48:34,800
positive and a negative face.

1194
00:48:34,800 --> 00:48:37,390
Here's another one where you're
doing positive and

1195
00:48:37,390 --> 00:48:38,870
negative car options,
things that are good

1196
00:48:38,870 --> 00:48:40,480
or bad about a car.

1197
00:48:40,480 --> 00:48:41,250
This line goes up.

1198
00:48:41,250 --> 00:48:41,960
This line goes down.

1199
00:48:41,960 --> 00:48:44,450
Younger people focus more on the
negative options relative

1200
00:48:44,450 --> 00:48:47,290
to older people who focus more
on the positive options.

1201
00:48:47,290 --> 00:48:48,100
Here's another one.

1202
00:48:48,100 --> 00:48:51,190
You show pictures of happy
scenes, or neutral scenes, are

1203
00:48:51,190 --> 00:48:51,950
negative scenes.

1204
00:48:51,950 --> 00:48:53,620
This is a graveyard.

1205
00:48:53,620 --> 00:48:57,180
Young people's memory for
positive, negative, and

1206
00:48:57,180 --> 00:48:59,800
neutral things, they remember
emotional things better.

1207
00:48:59,800 --> 00:49:00,770
Let's go to the older people.

1208
00:49:00,770 --> 00:49:02,420
Look at this line way up here.

1209
00:49:02,420 --> 00:49:04,110
That's memory for the
positive scenes.

1210
00:49:04,110 --> 00:49:05,630
And here's the negative
scenes.

1211
00:49:05,630 --> 00:49:08,610
Do you see the focus on the
positivity and the sort of

1212
00:49:08,610 --> 00:49:11,840
lack of interest in the
negative stuff?

1213
00:49:11,840 --> 00:49:14,060
For young people, equally
interesting if it's positive

1214
00:49:14,060 --> 00:49:14,620
or negative.

1215
00:49:14,620 --> 00:49:17,760
For older people, much more
interesting, and sticking in

1216
00:49:17,760 --> 00:49:18,950
your memory if it's positive.

1217
00:49:18,950 --> 00:49:22,690
And not sticking in your memory
if it's negative.

1218
00:49:22,690 --> 00:49:24,900
So one of the big questions
is, is this simply about

1219
00:49:24,900 --> 00:49:26,640
getting older?

1220
00:49:26,640 --> 00:49:29,460
And I'm going to ask you to
think back, if I can, to your

1221
00:49:29,460 --> 00:49:35,220
last days in high school, your
last days in high school.

1222
00:49:35,220 --> 00:49:36,940
For those last days--

1223
00:49:36,940 --> 00:49:38,990
and I'm sure it will vary
depending on your experience

1224
00:49:38,990 --> 00:49:40,836
in different ways--

1225
00:49:40,836 --> 00:49:43,670
were you primarily interested
in getting that last little

1226
00:49:43,670 --> 00:49:47,920
bit of information about
US history or calculus?

1227
00:49:47,920 --> 00:49:49,040
I mean, you might have been.

1228
00:49:49,040 --> 00:49:50,560
That could have been the
critical bit of information

1229
00:49:50,560 --> 00:49:53,390
that will make college
work out.

1230
00:49:53,390 --> 00:49:55,560
Or did you have a sudden--

1231
00:49:55,560 --> 00:49:58,050
and it's kind of embarrassing
when you're 16, 17, 18--

1232
00:49:58,050 --> 00:50:00,760
enhanced sense of nostalgia?

1233
00:50:00,760 --> 00:50:04,430
Oh, this is the last time the
three of us, or the six of us,

1234
00:50:04,430 --> 00:50:06,510
or the eight of us, or the two
of us will be together.

1235
00:50:06,510 --> 00:50:08,510
Then we're spreading across
the world to go

1236
00:50:08,510 --> 00:50:10,750
to different colleges.

1237
00:50:10,750 --> 00:50:12,400
Nobody had that feeling?

1238
00:50:12,400 --> 00:50:12,750
OK.

1239
00:50:12,750 --> 00:50:14,260
It's kind of embarrassing
when you're 18.

1240
00:50:14,260 --> 00:50:16,115
Because you're not supposed
to say that kind of stuff.

1241
00:50:16,115 --> 00:50:18,830
And it will happen to you at the
end the college for most

1242
00:50:18,830 --> 00:50:19,550
of you most of the time.

1243
00:50:19,550 --> 00:50:22,130
I remember senior year, it crept
up on us in college.

1244
00:50:22,130 --> 00:50:22,900
And we started college.

1245
00:50:22,900 --> 00:50:23,360
Oh my gosh.

1246
00:50:23,360 --> 00:50:24,330
This is the last year
we're together.

1247
00:50:24,330 --> 00:50:26,600
And it seemed very emotionally
important.

1248
00:50:26,600 --> 00:50:27,990
So age or time.

1249
00:50:27,990 --> 00:50:29,120
So is it simply age?

1250
00:50:29,120 --> 00:50:29,910
Or is it time?

1251
00:50:29,910 --> 00:50:32,400
So they did experiments where
they asked people, are you

1252
00:50:32,400 --> 00:50:34,720
focusing on adventure
and content?

1253
00:50:34,720 --> 00:50:37,210
Or are you focusing on emotion
and satisfaction?

1254
00:50:37,210 --> 00:50:39,260
When you're about to move from
one city to another, people

1255
00:50:39,260 --> 00:50:40,910
waned to spend time
with people they

1256
00:50:40,910 --> 00:50:41,860
really cared about.

1257
00:50:41,860 --> 00:50:43,120
And they were not interested
in getting new information.

1258
00:50:45,820 --> 00:50:48,550
Two more tragic studies, if
people are near death, and

1259
00:50:48,550 --> 00:50:50,890
they're asked this question,
of course time with people,

1260
00:50:50,890 --> 00:50:52,640
not acquiring information.

1261
00:50:52,640 --> 00:50:55,620
But here's another one,
inner-city gangs study in Los

1262
00:50:55,620 --> 00:50:59,340
Angeles, inner-city gangs
involved in violence are much

1263
00:50:59,340 --> 00:51:03,600
more interested in time with
people than in information.

1264
00:51:03,600 --> 00:51:07,300
And partly that goes with what
is viewed from the outside.

1265
00:51:07,300 --> 00:51:10,610
Sometimes this kind of insane
loyalty that inner-city gang

1266
00:51:10,610 --> 00:51:13,720
members have for one another is
because they're so focused

1267
00:51:13,720 --> 00:51:16,450
given their situation on this
relations with the other

1268
00:51:16,450 --> 00:51:19,640
people in their group compared
to everything that's rational

1269
00:51:19,640 --> 00:51:24,330
about a safe growing up.

1270
00:51:24,330 --> 00:51:26,810
And, tragically, you know if you
ask a member of inner-city

1271
00:51:26,810 --> 00:51:29,190
gangs how long they think
they'll live, they often tell

1272
00:51:29,190 --> 00:51:30,660
you not very long.

1273
00:51:30,660 --> 00:51:33,130
I'm counting on not
living very long.

1274
00:51:33,130 --> 00:51:36,580
So it's not whether you're
20, or 60, or 80.

1275
00:51:36,580 --> 00:51:39,210
It's how long you sense
time is in front of

1276
00:51:39,210 --> 00:51:43,270
you, a temporal horizon.

1277
00:51:43,270 --> 00:51:46,920
Here's one study that
I had a hand in.

1278
00:51:46,920 --> 00:51:49,650
We took older and younger people
and put them inside an

1279
00:51:49,650 --> 00:51:52,120
MRI and show them positive,
neutral,

1280
00:51:52,120 --> 00:51:52,830
and negative pictures.

1281
00:51:52,830 --> 00:51:54,530
Here's a couple different
points.

1282
00:51:54,530 --> 00:51:56,730
When they said, how intense
is this picture?

1283
00:51:56,730 --> 00:51:57,730
Look at younger people.

1284
00:51:57,730 --> 00:52:00,850
The positive, neutral, and the
negative are really intense.

1285
00:52:00,850 --> 00:52:01,850
This goes down.

1286
00:52:01,850 --> 00:52:04,930
So the older people, as they see
the pictures, experienced

1287
00:52:04,930 --> 00:52:07,780
by their own report, the
negative pictures as being

1288
00:52:07,780 --> 00:52:09,020
less intense.

1289
00:52:09,020 --> 00:52:11,470
They're sort of downplaying
the negative.

1290
00:52:11,470 --> 00:52:14,510
And if we asked their memory,
here's younger people.

1291
00:52:14,510 --> 00:52:17,250
Positive, and negative things,
neutral things, same for

1292
00:52:17,250 --> 00:52:17,950
positive and negative.

1293
00:52:17,950 --> 00:52:21,610
Look at older people, much
more focused in memory,

1294
00:52:21,610 --> 00:52:23,520
retaining in memory
the positive and

1295
00:52:23,520 --> 00:52:26,200
not so much the negative.

1296
00:52:26,200 --> 00:52:28,650
And if we look at their
amygdala, which we know is a

1297
00:52:28,650 --> 00:52:32,360
structure that's essential for
how emotion modulates the

1298
00:52:32,360 --> 00:52:35,320
formation of memory, here's
young people.

1299
00:52:35,320 --> 00:52:36,520
Here's a positive picture.

1300
00:52:36,520 --> 00:52:37,440
Here's a negative picture.

1301
00:52:37,440 --> 00:52:38,140
Here's a neutral picture.

1302
00:52:38,140 --> 00:52:39,610
So emotion counts.

1303
00:52:39,610 --> 00:52:42,520
Positive and negative count
about the same.

1304
00:52:42,520 --> 00:52:45,710
Look at older people.

1305
00:52:45,710 --> 00:52:47,900
Here's positive, and
here's negative.

1306
00:52:47,900 --> 00:52:50,670
So this partly addresses the
question for some people.

1307
00:52:50,670 --> 00:52:52,790
Are older people pretending
they're positive?

1308
00:52:52,790 --> 00:52:53,940
Well, it doesn't
look like that.

1309
00:52:53,940 --> 00:52:55,620
This is their amygdala as
they're looking at it.

1310
00:52:55,620 --> 00:52:57,520
I don't know if their
amygdala can pretend

1311
00:52:57,520 --> 00:52:59,300
to look at the positive.

1312
00:52:59,300 --> 00:53:01,390
So here's the good
news for you.

1313
00:53:01,390 --> 00:53:04,620
What will happen as you get
older, on average, is that for

1314
00:53:04,620 --> 00:53:08,000
whatever reason it happens-- and
we don't really know why--

1315
00:53:08,000 --> 00:53:10,050
you will focus more and
more on the positive

1316
00:53:10,050 --> 00:53:11,310
things in your life.

1317
00:53:11,310 --> 00:53:15,640
And you'll feel better
for that, on average.

1318
00:53:15,640 --> 00:53:18,850
So that's the kind of
quiet satisfaction.

1319
00:53:18,850 --> 00:53:20,495
Now I'm focusing on
the positive.

1320
00:53:20,495 --> 00:53:22,050
That's the zen satisfaction.

1321
00:53:22,050 --> 00:53:25,890
Let's talk about fantastic
satisfaction, reward system.

1322
00:53:25,890 --> 00:53:28,580
When you really want to do
something, because it's going

1323
00:53:28,580 --> 00:53:30,690
to feel so wonderful,
the reward system.

1324
00:53:30,690 --> 00:53:32,220
So let me tell you a little bit
about what we understand

1325
00:53:32,220 --> 00:53:33,550
about that.

1326
00:53:33,550 --> 00:53:36,560
It involves dopamine as the
critical neurotransmitter.

1327
00:53:36,560 --> 00:53:38,700
It starts in the ventral
tegmental

1328
00:53:38,700 --> 00:53:40,040
area of your brainstem.

1329
00:53:40,040 --> 00:53:42,140
And that projects to something
called the nucleus accumbens,

1330
00:53:42,140 --> 00:53:44,620
an inferior portion of
the basal ganglia.

1331
00:53:44,620 --> 00:53:47,330
And this is reward central.

1332
00:53:47,330 --> 00:53:51,190
If you love something from
opera, to chocolate, to video

1333
00:53:51,190 --> 00:53:53,290
games, this turns on.

1334
00:53:53,290 --> 00:53:57,070
Every experiment that people
have ever done shows in humans

1335
00:53:57,070 --> 00:54:00,310
if something really turns
you on, this area

1336
00:54:00,310 --> 00:54:02,180
really gets turned on.

1337
00:54:02,180 --> 00:54:05,470
What's more powerful for us
than what we find deeply

1338
00:54:05,470 --> 00:54:07,280
emotionally rewarding?

1339
00:54:07,280 --> 00:54:10,890
This is that rewards system.

1340
00:54:10,890 --> 00:54:13,520
And the dopamine runs
from there.

1341
00:54:13,520 --> 00:54:14,690
And look at how cells respond.

1342
00:54:14,690 --> 00:54:16,490
I'm going to show you an example
from monkeys where we

1343
00:54:16,490 --> 00:54:17,900
can look at single cells.

1344
00:54:17,900 --> 00:54:20,920
And then brain imaging,
back to people.

1345
00:54:20,920 --> 00:54:23,020
So here's the experiment
with monkeys.

1346
00:54:23,020 --> 00:54:25,600
And there's a message in this
that's both biologically true

1347
00:54:25,600 --> 00:54:28,500
and compelling about
human life.

1348
00:54:28,500 --> 00:54:30,850
So what's biologically true in
science what's compelling

1349
00:54:30,850 --> 00:54:33,470
about life is a story.

1350
00:54:33,470 --> 00:54:34,970
So here's the experiment.

1351
00:54:34,970 --> 00:54:38,300
The monkey sits there and gets
various cues, different visual

1352
00:54:38,300 --> 00:54:40,090
things that tell them
what's coming up.

1353
00:54:40,090 --> 00:54:42,420
Let's pretend this is a cue
that's something wonderful is

1354
00:54:42,420 --> 00:54:45,610
coming up, highly
desired food.

1355
00:54:45,610 --> 00:54:47,380
So they're recording
electrically why

1356
00:54:47,380 --> 00:54:48,720
the animal sees this.

1357
00:54:48,720 --> 00:54:52,490
There's waiting for what we call
the anticipation period.

1358
00:54:52,490 --> 00:54:54,080
And now here comes the reward.

1359
00:54:54,080 --> 00:54:56,700
And here's something sort of
deep, I think, about reward,

1360
00:54:56,700 --> 00:54:59,170
and learning, and people,
and things like this.

1361
00:54:59,170 --> 00:55:01,440
So here's the neurons firing.

1362
00:55:01,440 --> 00:55:03,840
This is the sum of the neurons
firing in the ventral

1363
00:55:03,840 --> 00:55:05,010
tegmental area.

1364
00:55:05,010 --> 00:55:07,230
So right now they're
just sitting there.

1365
00:55:07,230 --> 00:55:10,140
Oops, here comes the reward.

1366
00:55:10,140 --> 00:55:12,610
And boom, dopamine
is released.

1367
00:55:12,610 --> 00:55:14,450
The dopaminergic cells are
firing like crazy.

1368
00:55:14,450 --> 00:55:15,870
They're getting food
they really want.

1369
00:55:15,870 --> 00:55:17,170
We're thrilled.

1370
00:55:17,170 --> 00:55:20,150
We're hungry, and we're getting
something delicious.

1371
00:55:20,150 --> 00:55:22,230
Not much more rewarding
can happen when

1372
00:55:22,230 --> 00:55:23,910
you're really hungry.

1373
00:55:23,910 --> 00:55:28,110
Now they predict the arrival
with the cue that you saw, a

1374
00:55:28,110 --> 00:55:31,650
meaningless stimulus.

1375
00:55:31,650 --> 00:55:32,330
And look what happens.

1376
00:55:32,330 --> 00:55:34,250
When do these neurons fire?

1377
00:55:34,250 --> 00:55:37,900
Not for the food arriving, but
for the visual signal that

1378
00:55:37,900 --> 00:55:40,060
predicts the food will come.

1379
00:55:40,060 --> 00:55:44,500
What's delicious for the brain
is the anticipation of

1380
00:55:44,500 --> 00:55:46,360
something that's rewarding.

1381
00:55:46,360 --> 00:55:47,843
And this morning when I was
thinking about this lecture, I

1382
00:55:47,843 --> 00:55:50,370
was thinking.

1383
00:55:50,370 --> 00:55:51,370
You might say this.

1384
00:55:51,370 --> 00:55:52,765
Think about experiences
you've had that you've

1385
00:55:52,765 --> 00:55:53,440
looked forward to.

1386
00:55:53,440 --> 00:55:55,710
And almost the most delicious
part, you might say, is the

1387
00:55:55,710 --> 00:55:57,660
anticipation of something
delightful.

1388
00:55:57,660 --> 00:56:02,600
Often the event itself is more
mixed and anticlimactic than

1389
00:56:02,600 --> 00:56:03,570
you would've thought.

1390
00:56:03,570 --> 00:56:05,050
Is that fair?

1391
00:56:05,050 --> 00:56:06,950
I think there's nothing better
like I'm anticipating

1392
00:56:06,950 --> 00:56:07,510
something wonderful.

1393
00:56:07,510 --> 00:56:08,910
And the event can
be wonderful.

1394
00:56:08,910 --> 00:56:10,810
But often it's a little
more complicated.

1395
00:56:10,810 --> 00:56:13,910
That anticipation is like
pure joy, because you're

1396
00:56:13,910 --> 00:56:18,510
dopaminergic system is
firing freely away.

1397
00:56:18,510 --> 00:56:20,040
And it protests also.

1398
00:56:20,040 --> 00:56:22,200
So you get the visual
signal that, oh, the

1399
00:56:22,200 --> 00:56:25,300
reward's coming up.

1400
00:56:25,300 --> 00:56:26,000
Here it is.

1401
00:56:26,000 --> 00:56:27,730
Here comes the food.

1402
00:56:27,730 --> 00:56:28,960
The food doesn't come.

1403
00:56:28,960 --> 00:56:30,620
Look at the silence.

1404
00:56:30,620 --> 00:56:33,960
These cells are protesting
because they didn't get what

1405
00:56:33,960 --> 00:56:36,160
they expected to get.

1406
00:56:36,160 --> 00:56:40,270
So it's very compelling that the
reward in you occurs not

1407
00:56:40,270 --> 00:56:44,020
even so much for the reward
itself, but the anticipation

1408
00:56:44,020 --> 00:56:47,040
of the reward is where it's
biologically occurring when

1409
00:56:47,040 --> 00:56:50,120
you can anticipate and count
on it correctly.

1410
00:56:50,120 --> 00:56:53,240
So, in humans, it's harder to
deliver-- not impossible--

1411
00:56:53,240 --> 00:56:54,050
food in a scanner.

1412
00:56:54,050 --> 00:56:57,010
So a very simple thing is done
for a reward, which is

1413
00:56:57,010 --> 00:56:58,350
offering people money.

1414
00:56:58,350 --> 00:57:00,520
So in a given trial on a
scanner, you might see a

1415
00:57:00,520 --> 00:57:01,600
meaningless cue like this.

1416
00:57:01,600 --> 00:57:06,320
But you learn that this box
predicts that at the end of

1417
00:57:06,320 --> 00:57:07,340
this trial--

1418
00:57:07,340 --> 00:57:08,430
you do many trials--

1419
00:57:08,430 --> 00:57:09,940
you're going to get $1.00.

1420
00:57:09,940 --> 00:57:10,770
Another one might be $0.10.

1421
00:57:10,770 --> 00:57:13,090
Another one they might
take away $1.00.

1422
00:57:13,090 --> 00:57:14,280
So this is like a
good one to get.

1423
00:57:14,280 --> 00:57:15,945
I'm going to get $1
just sitting here.

1424
00:57:15,945 --> 00:57:17,910
I'm going to get $1.

1425
00:57:17,910 --> 00:57:18,700
It's not huge.

1426
00:57:18,700 --> 00:57:20,990
It's not the biggest reward
in the world.

1427
00:57:20,990 --> 00:57:22,310
But it's something for
just laying in the

1428
00:57:22,310 --> 00:57:24,830
scanner doing nothing.

1429
00:57:24,830 --> 00:57:26,840
And here's what happens.

1430
00:57:26,840 --> 00:57:29,740
Your nucleus accumbens gets
activated, where dopamine

1431
00:57:29,740 --> 00:57:32,480
flows from the ventral tegmental
area when you

1432
00:57:32,480 --> 00:57:34,890
anticipate a reward.

1433
00:57:34,890 --> 00:57:36,200
This is not when the
reward comes.

1434
00:57:36,200 --> 00:57:39,250
This is when you're anticipating
the reward.

1435
00:57:39,250 --> 00:57:41,600
Here's another picture.

1436
00:57:41,600 --> 00:57:43,560
It's most powerful
for when people

1437
00:57:43,560 --> 00:57:45,350
anticipate a gain, a reward.

1438
00:57:45,350 --> 00:57:49,140
And it's less responsive when
people anticipate a loss.

1439
00:57:49,140 --> 00:57:51,880
So it's about gains.

1440
00:57:51,880 --> 00:57:54,970
Then the same system projects to
the inferior parts of your

1441
00:57:54,970 --> 00:57:56,980
frontal lobe.

1442
00:57:56,980 --> 00:57:59,110
So now we're moving into
the neocortex.

1443
00:57:59,110 --> 00:58:01,920
And that part of the brain
seems to respond most

1444
00:58:01,920 --> 00:58:04,080
powerfully if you
get the reward.

1445
00:58:04,080 --> 00:58:05,970
So this is really interesting,
a part of your brain that

1446
00:58:05,970 --> 00:58:07,960
responds to the anticipation,
the

1447
00:58:07,960 --> 00:58:09,510
dopaminergic reward system.

1448
00:58:09,510 --> 00:58:11,660
And then another part of their
brain that responds not

1449
00:58:11,660 --> 00:58:12,450
whether you anticipate it.

1450
00:58:12,450 --> 00:58:13,470
But sometimes they trick you.

1451
00:58:13,470 --> 00:58:14,470
They say we're going
to give you $1.

1452
00:58:14,470 --> 00:58:14,840
And then they go, oops.

1453
00:58:14,840 --> 00:58:16,410
We're not giving it to you.

1454
00:58:16,410 --> 00:58:19,300
This part of the brain seems to
register the receipt of the

1455
00:58:19,300 --> 00:58:19,960
reward or not.

1456
00:58:19,960 --> 00:58:21,710
So there's a separation of the
brain between the anticipation

1457
00:58:21,710 --> 00:58:23,700
of the reward and the response
to whether you get

1458
00:58:23,700 --> 00:58:24,950
the reward or not.

1459
00:58:28,100 --> 00:58:30,920
Older people, when they look
at these kinds of similar

1460
00:58:30,920 --> 00:58:35,330
reward paradigms, they're less
responsive to potential loss

1461
00:58:35,330 --> 00:58:36,880
but equally responsive
to potential

1462
00:58:36,880 --> 00:58:38,750
gain as young adults.

1463
00:58:38,750 --> 00:58:42,060
So that's exactly responding to
positive things and showing

1464
00:58:42,060 --> 00:58:46,440
less of a response to potential
negative things.

1465
00:58:46,440 --> 00:58:48,440
So let's switch to
adolescents.

1466
00:58:48,440 --> 00:58:50,480
We're going to focus on
adolescents now mostly for the

1467
00:58:50,480 --> 00:58:53,360
next 10 minutes.

1468
00:58:53,360 --> 00:58:54,910
You just got through that.

1469
00:58:54,910 --> 00:58:57,000
So let's reflect back for the
last couple of years.

1470
00:58:57,000 --> 00:58:58,680
And they make the experiments
because they want to put

1471
00:58:58,680 --> 00:59:00,350
children into a little
bit more of a vivid.

1472
00:59:00,350 --> 00:59:01,060
Here's pirates.

1473
00:59:01,060 --> 00:59:02,430
Here's not much reward.

1474
00:59:02,430 --> 00:59:03,040
Here's some reward.

1475
00:59:03,040 --> 00:59:05,300
Here's a lot of reward
in the scanner.

1476
00:59:05,300 --> 00:59:08,830
And your children are
adolescents or young adults.

1477
00:59:08,830 --> 00:59:10,340
And they look in the
nucleus accumbens.

1478
00:59:10,340 --> 00:59:11,470
This is that reward region.

1479
00:59:11,470 --> 00:59:13,720
And look who's firing
like crazy?

1480
00:59:13,720 --> 00:59:17,540
Adolescents, teenagers.

1481
00:59:17,540 --> 00:59:19,840
But they're not firing like
crazy in the frontal cortex.

1482
00:59:22,520 --> 00:59:25,570
So this is very speculative.

1483
00:59:25,570 --> 00:59:27,990
These are partly just
wide stories.

1484
00:59:27,990 --> 00:59:30,000
But one hypothesis is this.

1485
00:59:30,000 --> 00:59:33,120
And we're going to say in a
minute more about this.

1486
00:59:33,120 --> 00:59:36,000
Adolescence is a really
interesting period.

1487
00:59:36,000 --> 00:59:38,790
Because it's not only when
you're deciding who you are in

1488
00:59:38,790 --> 00:59:40,800
the world in many ways
independently.

1489
00:59:40,800 --> 00:59:44,640
It's also, worrisomely for
parents, grandparents,

1490
00:59:44,640 --> 00:59:48,180
cousins, siblings, the period
in life when people are most

1491
00:59:48,180 --> 00:59:51,730
likely to put themselves
at great risk.

1492
00:59:51,730 --> 00:59:56,430
And one version of that is that
the subcortical reward

1493
00:59:56,430 --> 01:00:01,040
areas are developing way faster
than the cortical areas

1494
01:00:01,040 --> 01:00:05,970
that control and regulate
your behavior.

1495
01:00:05,970 --> 01:00:09,200
This goes with the stereotype
which is probably as unfair as

1496
01:00:09,200 --> 01:00:13,146
any other stereotype of the
out of control teenager.

1497
01:00:13,146 --> 01:00:15,810
But imagine if it were true
that your reward system is

1498
01:00:15,810 --> 01:00:17,510
very turned up.

1499
01:00:17,510 --> 01:00:20,550
And your cortical control system
were not yet caught up

1500
01:00:20,550 --> 01:00:21,770
to the adult level.

1501
01:00:21,770 --> 01:00:23,730
Well, that would make you a
little bit more likely to do

1502
01:00:23,730 --> 01:00:25,620
adventuresome things.

1503
01:00:25,620 --> 01:00:27,390
Because the reward
is powerful.

1504
01:00:27,390 --> 01:00:30,340
And the control of your thoughts
about how to approach

1505
01:00:30,340 --> 01:00:32,330
or reject that reward
are less powerful.

1506
01:00:35,940 --> 01:00:38,130
So here's some things
to think about.

1507
01:00:38,130 --> 01:00:41,000
And people worry about
for adolescents.

1508
01:00:41,000 --> 01:00:43,970
40% of adult alcoholics report
having initial alcoholism

1509
01:00:43,970 --> 01:00:45,200
between 15 and 19.

1510
01:00:45,200 --> 01:00:49,120
Between 16 and 20, both sexes
are twice as likely to be in

1511
01:00:49,120 --> 01:00:51,550
accidents than drivers between
20 and 50, twice the

1512
01:00:51,550 --> 01:00:52,920
accidental rate.

1513
01:00:52,920 --> 01:00:55,270
Adolescents are more likely to
engage in impulsive sexual

1514
01:00:55,270 --> 01:00:57,280
behavior and multiple
partners.

1515
01:00:57,280 --> 01:00:59,770
Annually, three million
adolescents contract a sexual

1516
01:00:59,770 --> 01:01:00,680
transmitted disease.

1517
01:01:00,680 --> 01:01:04,710
So lots of things that are risky
behaviors occur with

1518
01:01:04,710 --> 01:01:07,830
high frequency in a demonstrable
way, on average,

1519
01:01:07,830 --> 01:01:09,840
among adolescents.

1520
01:01:09,840 --> 01:01:12,150
Young kids don't drive yet.

1521
01:01:12,150 --> 01:01:15,730
20-year-olds are a bit more
mature in their driving.

1522
01:01:15,730 --> 01:01:20,350
So part of this is, again,
attitudinal.

1523
01:01:20,350 --> 01:01:22,720
Here's a question that people
were asked about future

1524
01:01:22,720 --> 01:01:23,610
perspectives.

1525
01:01:23,610 --> 01:01:25,970
They were asked, I would rather
save my money for a

1526
01:01:25,970 --> 01:01:29,930
rainy day than spend it on
something fun right now.

1527
01:01:32,560 --> 01:01:34,030
In your 20s, a little bit.

1528
01:01:37,660 --> 01:01:38,700
That's growing.

1529
01:01:38,700 --> 01:01:40,020
You'll keep the dollar.

1530
01:01:40,020 --> 01:01:42,590
But the younger you are in your
teenage years, the more

1531
01:01:42,590 --> 01:01:44,080
like who wants to wait.

1532
01:01:44,080 --> 01:01:46,620
Let's do it now.

1533
01:01:46,620 --> 01:01:50,660
So moving from something fun
to something experimental,

1534
01:01:50,660 --> 01:01:52,910
let's put together a
couple last things.

1535
01:01:52,910 --> 01:01:55,420
So here's a thing we did before
several times in this

1536
01:01:55,420 --> 01:01:57,800
class, creating false
memories.

1537
01:01:57,800 --> 01:01:59,950
And you remember the way they
create false memories in the

1538
01:01:59,950 --> 01:02:02,870
laboratory is they pick a word
they don't present to you,

1539
01:02:02,870 --> 01:02:04,072
like sweet.

1540
01:02:04,072 --> 01:02:06,960
Then they ask many students to
say what words go with that

1541
01:02:06,960 --> 01:02:08,360
word, like sour, or
candy, or sugar?

1542
01:02:08,360 --> 01:02:10,540
They present you this list.

1543
01:02:10,540 --> 01:02:11,940
And then they test
you for this word

1544
01:02:11,940 --> 01:02:13,370
that was not presented.

1545
01:02:13,370 --> 01:02:17,890
And people often imagine
incorrectly that they heard or

1546
01:02:17,890 --> 01:02:18,750
saw this word.

1547
01:02:18,750 --> 01:02:20,060
We've done that a
couple of times.

1548
01:02:20,060 --> 01:02:22,700
It's a way to show
illusory memory.

1549
01:02:22,700 --> 01:02:24,810
And the way we understand
it is basically this.

1550
01:02:24,810 --> 01:02:29,520
Your memory, your mind, mostly
thinks about the essence of

1551
01:02:29,520 --> 01:02:31,750
things, not the details
of things.

1552
01:02:31,750 --> 01:02:34,790
The essence of things was
everything is sweet.

1553
01:02:34,790 --> 01:02:38,820
The details were the specific
words in the list.

1554
01:02:38,820 --> 01:02:43,680
So let's look at older adults
versus younger adults,

1555
01:02:43,680 --> 01:02:45,450
80-year-olds versus 20-year-olds
and exactly this

1556
01:02:45,450 --> 01:02:46,310
experiment.

1557
01:02:46,310 --> 01:02:48,280
Older adults have many
more false memories.

1558
01:02:48,280 --> 01:02:50,110
And they perform less well.

1559
01:02:50,110 --> 01:02:54,480
So to a scary extend, the
healthy 70-year-olds, here's

1560
01:02:54,480 --> 01:02:55,220
their real memories.

1561
01:02:55,220 --> 01:02:56,460
Here's their false memories.

1562
01:02:56,460 --> 01:02:58,640
It's dead even.

1563
01:02:58,640 --> 01:03:00,610
Here's young people having lots
of false memories, but

1564
01:03:00,610 --> 01:03:02,380
not as many as older
people, and having

1565
01:03:02,380 --> 01:03:04,010
more correct memories.

1566
01:03:04,010 --> 01:03:07,310
So older adults have more
false memories, because

1567
01:03:07,310 --> 01:03:09,780
they're encoding the
gist a lot, but

1568
01:03:09,780 --> 01:03:10,950
they're losing the specifics.

1569
01:03:10,950 --> 01:03:11,480
Does that make sense?

1570
01:03:11,480 --> 01:03:13,190
And you're really vulnerable
to false memories.

1571
01:03:15,820 --> 01:03:17,930
Children, you might think,
well children,

1572
01:03:17,930 --> 01:03:18,890
what do they know?

1573
01:03:18,890 --> 01:03:21,790
Children have less false
memories than you do.

1574
01:03:21,790 --> 01:03:25,420
You would have less false
memories at age five than you

1575
01:03:25,420 --> 01:03:27,640
would right now, which
is kind of amazing.

1576
01:03:27,640 --> 01:03:29,220
If you didn't do the experiment,
you'd imagine

1577
01:03:29,220 --> 01:03:30,880
children would be totally
confused.

1578
01:03:30,880 --> 01:03:31,890
They'd get a big
list of words.

1579
01:03:31,890 --> 01:03:32,830
Was sweet on the list?

1580
01:03:32,830 --> 01:03:33,190
I don't know.

1581
01:03:33,190 --> 01:03:34,660
Yeah, sure.

1582
01:03:34,660 --> 01:03:37,160
A five-year-old does better than
a seven, does better than

1583
01:03:37,160 --> 01:03:40,820
an 11-year-old, does better
than a 20-year-old.

1584
01:03:40,820 --> 01:03:42,200
Why?

1585
01:03:42,200 --> 01:03:44,970
Why does a five-year-old have
less false memories under the

1586
01:03:44,970 --> 01:03:46,310
circumstances?

1587
01:03:46,310 --> 01:03:51,370
Well, we understand that to be
the price of having a mind

1588
01:03:51,370 --> 01:03:53,180
that understands
a lot of gist.

1589
01:03:53,180 --> 01:03:55,580
As you become older, you
understand what's important,

1590
01:03:55,580 --> 01:03:56,090
what counts.

1591
01:03:56,090 --> 01:03:57,540
It's not the little details.

1592
01:03:57,540 --> 01:04:00,110
It's the big concepts.

1593
01:04:00,110 --> 01:04:02,900
So here's an example of, for
example, how well people can

1594
01:04:02,900 --> 01:04:05,550
relate words across sentences.

1595
01:04:05,550 --> 01:04:08,590
And that grows from
six to nine.

1596
01:04:08,590 --> 01:04:09,320
And that's what we want.

1597
01:04:09,320 --> 01:04:11,620
You don't want to read
word, word, word.

1598
01:04:11,620 --> 01:04:15,640
You want to say, what's the
point of the sentence?

1599
01:04:15,640 --> 01:04:18,380
That process of saying, I don't
care about the detail.

1600
01:04:18,380 --> 01:04:23,600
I care about the concept, the
gist of the concept, it's like

1601
01:04:23,600 --> 01:04:24,220
the chess players.

1602
01:04:24,220 --> 01:04:27,320
You shed the specific
details to gain the

1603
01:04:27,320 --> 01:04:29,050
overall knowledge advantage.

1604
01:04:29,050 --> 01:04:32,130
But the five-year-old is not
making the big picture.

1605
01:04:32,130 --> 01:04:33,440
They're just getting
the little details.

1606
01:04:33,440 --> 01:04:38,395
So they're less prone to
the illusory memories.

1607
01:04:38,395 --> 01:04:39,310
We can't see that.

1608
01:04:39,310 --> 01:04:41,420
But this is just showing that
when it comes to organizing

1609
01:04:41,420 --> 01:04:46,650
memories, you see that develop
across a childhood.

1610
01:04:46,650 --> 01:04:47,370
Last couple of things.

1611
01:04:47,370 --> 01:04:49,070
Because when I heard this a few
years ago at a conference,

1612
01:04:49,070 --> 01:04:50,540
I was so surprised by
these findings.

1613
01:04:50,540 --> 01:04:52,160
And I've been around long enough
that i don't get as

1614
01:04:52,160 --> 01:04:54,000
surprised as often
as I used to.

1615
01:04:54,000 --> 01:04:55,100
But it's kind of really
interesting.

1616
01:04:55,100 --> 01:04:56,490
It's a total twist.

1617
01:04:56,490 --> 01:04:58,700
And you can make a judgment
call about how

1618
01:04:58,700 --> 01:04:59,280
to interpret it.

1619
01:04:59,280 --> 01:05:01,060
But here's the experiments
and the data.

1620
01:05:01,060 --> 01:05:02,770
So, again, we have this picture
that everybody likes

1621
01:05:02,770 --> 01:05:06,290
because it fits with the
stereotype, which is the

1622
01:05:06,290 --> 01:05:07,600
teenager out of control.

1623
01:05:07,600 --> 01:05:09,190
Their dopamine is going up.

1624
01:05:09,190 --> 01:05:12,460
And they're saying, let's do a
lot of inappropriate things.

1625
01:05:12,460 --> 01:05:14,810
Because it will be rewarding.

1626
01:05:14,810 --> 01:05:16,780
I know everybody's against it.

1627
01:05:16,780 --> 01:05:17,740
So that's the stereotype.

1628
01:05:17,740 --> 01:05:19,550
And probably there's something
true about that.

1629
01:05:19,550 --> 01:05:20,730
Literally, in the brain
imaging, it

1630
01:05:20,730 --> 01:05:23,010
looks somewhat true.

1631
01:05:23,010 --> 01:05:24,680
But let's think about
this for a moment.

1632
01:05:24,680 --> 01:05:25,760
You're going to be
good at this.

1633
01:05:25,760 --> 01:05:26,660
If line a--

1634
01:05:26,660 --> 01:05:28,960
these are lines-- is longer than
b, and line b is longer

1635
01:05:28,960 --> 01:05:32,100
than line c, is a
longer than c?

1636
01:05:32,100 --> 01:05:32,470
Yes.

1637
01:05:32,470 --> 01:05:32,990
All right.

1638
01:05:32,990 --> 01:05:34,240
This is MIT.

1639
01:05:37,370 --> 01:05:40,120
Now answer this question
truly.

1640
01:05:40,120 --> 01:05:41,530
Think about it for a moment.

1641
01:05:41,530 --> 01:05:43,040
Person a is a friend
or person b.

1642
01:05:43,040 --> 01:05:45,070
So let's pretend you're person
b and your friend was a.

1643
01:05:45,070 --> 01:05:46,015
You're also a friend with c.

1644
01:05:46,015 --> 01:05:49,410
Are a and c likely
to be friends?

1645
01:05:49,410 --> 01:05:50,450
Let's think about this.

1646
01:05:50,450 --> 01:05:53,660
Is it mathematically transitive
like this one?

1647
01:05:53,660 --> 01:05:54,720
No.

1648
01:05:54,720 --> 01:05:56,100
Let's think about
it for a moment.

1649
01:05:56,100 --> 01:06:00,630
In your experience through life,
on average, are your

1650
01:06:00,630 --> 01:06:03,940
friends mostly kind of going
to like each other?

1651
01:06:03,940 --> 01:06:07,800
Kind of, not all the
time, but kind of?

1652
01:06:07,800 --> 01:06:08,500
Yeah, probably.

1653
01:06:08,500 --> 01:06:11,670
Because if one person likes you,
and another person likes

1654
01:06:11,670 --> 01:06:12,620
you, you share interests.

1655
01:06:12,620 --> 01:06:15,660
You share background to a
certain extent, in a loose

1656
01:06:15,660 --> 01:06:16,610
statistical way.

1657
01:06:16,610 --> 01:06:17,840
It's not definitive like this.

1658
01:06:17,840 --> 01:06:19,250
So let's take a look at what
happens when you ask you two

1659
01:06:19,250 --> 01:06:21,890
questions to grades
one through four.

1660
01:06:21,890 --> 01:06:23,950
OK, these kids are just
making mistakes.

1661
01:06:23,950 --> 01:06:24,920
And they're getting smarter.

1662
01:06:24,920 --> 01:06:28,120
But look at this one go
up just like that.

1663
01:06:28,120 --> 01:06:32,050
So we can say this is a growth
in logical ability.

1664
01:06:32,050 --> 01:06:36,120
This is a growth in your
everyday sense that I hang out

1665
01:06:36,120 --> 01:06:37,540
with a certain kind of person.

1666
01:06:37,540 --> 01:06:39,130
Maybe they like football.

1667
01:06:39,130 --> 01:06:41,590
Maybe they like skating.

1668
01:06:41,590 --> 01:06:43,750
Maybe they like psychology.

1669
01:06:43,750 --> 01:06:45,520
but that's the group I tend
to hang out with.

1670
01:06:45,520 --> 01:06:49,630
And, on average, if I have a
friend, it's because we share

1671
01:06:49,630 --> 01:06:52,370
some interests, or
style of being.

1672
01:06:52,370 --> 01:06:54,480
And if I have another friend,
we probably share that too.

1673
01:06:54,480 --> 01:07:00,790
So more than chance, they
might like each other.

1674
01:07:00,790 --> 01:07:03,460
So this is this idea that you
can separate out what you

1675
01:07:03,460 --> 01:07:07,600
might call purely logical
analysis of things versus a

1676
01:07:07,600 --> 01:07:10,930
growth of social experience,
basically.

1677
01:07:10,930 --> 01:07:14,240
So the last three
slides or so.

1678
01:07:14,240 --> 01:07:16,520
You remember this from a bit
back, from a prior example.

1679
01:07:16,520 --> 01:07:18,000
We said there's a framing
heuristic.

1680
01:07:21,210 --> 01:07:22,550
People are risk averse
for gains.

1681
01:07:22,550 --> 01:07:24,370
But they're risk-taking
for losses.

1682
01:07:24,370 --> 01:07:25,750
If we said here's a program.

1683
01:07:25,750 --> 01:07:26,810
We did this before.

1684
01:07:26,810 --> 01:07:31,760
If Program A is adopted,
200 people are saved.

1685
01:07:31,760 --> 01:07:33,760
Or here's 400 people will
die out of 600.

1686
01:07:33,760 --> 01:07:35,630
That's the same statement.

1687
01:07:35,630 --> 01:07:39,400
But because this is stated
as a gain, people

1688
01:07:39,400 --> 01:07:40,520
usually like this.

1689
01:07:40,520 --> 01:07:42,980
Because this is stated
as a loss, people

1690
01:07:42,980 --> 01:07:44,180
usually don't like this.

1691
01:07:44,180 --> 01:07:47,750
Adults are risk averse for
gains, and they're risk-taking

1692
01:07:47,750 --> 01:07:48,295
for losses.

1693
01:07:48,295 --> 01:07:50,570
If something looks like
a loss, roll the dice.

1694
01:07:50,570 --> 01:07:53,370
If something looks like it's
going to work out, go with it,

1695
01:07:53,370 --> 01:07:55,170
even though numerically,
these are identical.

1696
01:07:58,500 --> 01:07:59,400
You can't see this.

1697
01:07:59,400 --> 01:08:01,040
I can tell you.

1698
01:08:01,040 --> 01:08:04,190
It's not present in

1699
01:08:04,190 --> 01:08:06,160
preschoolers or second graders.

1700
01:08:06,160 --> 01:08:08,390
Preschoolers or second graders,
when you give them

1701
01:08:08,390 --> 01:08:11,960
these kinds of problems, they
don't show the asymmetry for

1702
01:08:11,960 --> 01:08:13,560
losses and gains.

1703
01:08:13,560 --> 01:08:15,940
That's something that
happens over time.

1704
01:08:15,940 --> 01:08:16,950
And it's not a logical one.

1705
01:08:16,950 --> 01:08:18,450
Logically, it should be that.

1706
01:08:18,450 --> 01:08:22,330
So in that weird sense, the
preschooler is more logical

1707
01:08:22,330 --> 01:08:25,979
than you and I, more logical
than you and I. Because

1708
01:08:25,979 --> 01:08:27,830
there's no reason to be
statistically different for

1709
01:08:27,830 --> 01:08:28,689
losses and gains.

1710
01:08:28,689 --> 01:08:32,250
That's purely an attitudinal
emotional perspective.

1711
01:08:32,250 --> 01:08:33,680
First of all, you can hear
the information-seeking.

1712
01:08:33,680 --> 01:08:34,460
Let's check it out.

1713
01:08:34,460 --> 01:08:37,770
That's kind of interesting,
swimming with sharks.

1714
01:08:37,770 --> 01:08:40,830
I can assure you 70-year-olds
are not going to go, hey, that

1715
01:08:40,830 --> 01:08:41,539
can be kind of interesting.

1716
01:08:41,539 --> 01:08:42,370
They're going, no!

1717
01:08:42,370 --> 01:08:42,840
Terrible idea!

1718
01:08:42,840 --> 01:08:43,770
Don't do it!

1719
01:08:43,770 --> 01:08:46,006
Yeah?

1720
01:08:46,006 --> 01:08:48,880
AUDIENCE: Were they asked
in a group collectively?

1721
01:08:48,880 --> 01:08:49,359
PROFESSOR: Yeah.

1722
01:08:49,359 --> 01:08:51,540
You see some peer influence.

1723
01:08:51,540 --> 01:08:52,310
Yeah.

1724
01:08:52,310 --> 01:08:54,290
And that doesn't happen with
adolescents, right?

1725
01:08:58,890 --> 01:08:59,170
They do this.

1726
01:08:59,170 --> 01:08:59,990
They go, oh my gosh.

1727
01:08:59,990 --> 01:09:01,550
These are these teenagers who
are going to go do all these

1728
01:09:01,550 --> 01:09:03,870
things, and get horrible sexual
diseases, and drive

1729
01:09:03,870 --> 01:09:05,149
while they are impaired.

1730
01:09:05,149 --> 01:09:08,420
And that's just the beginning
of their weekend.

1731
01:09:08,420 --> 01:09:10,370
Because they're not going to
follow all the advice that we

1732
01:09:10,370 --> 01:09:11,950
gave them for years, and years,
and years, and years,

1733
01:09:11,950 --> 01:09:13,510
at home and in school.

1734
01:09:13,510 --> 01:09:15,170
So here's the flip on this.

1735
01:09:15,170 --> 01:09:17,430
And just think about
it for a moment.

1736
01:09:17,430 --> 01:09:19,100
It's complicated.

1737
01:09:19,100 --> 01:09:22,350
Swimming with sharks, the adults
say, you don't have to

1738
01:09:22,350 --> 01:09:23,050
tell me any more.

1739
01:09:23,050 --> 01:09:24,300
It's a bad idea.

1740
01:09:24,300 --> 01:09:27,160
The gist is sharks, bad.

1741
01:09:27,160 --> 01:09:29,450
I don't even need to hear
the rest of the story.

1742
01:09:29,450 --> 01:09:31,890
Adolescents start to
weigh the factors.

1743
01:09:31,890 --> 01:09:33,140
We'd be safer in a group.

1744
01:09:33,140 --> 01:09:35,620
Is it dark or night outside?

1745
01:09:35,620 --> 01:09:38,370
How shallow is the water?

1746
01:09:38,370 --> 01:09:40,500
And you can say, well, it's
kind of ridiculous.

1747
01:09:40,500 --> 01:09:42,120
But it's not totally
ridiculous.

1748
01:09:42,120 --> 01:09:44,500
Because when we talk about
danger, those are some of the

1749
01:09:44,500 --> 01:09:46,109
things you might start
to think about.

1750
01:09:46,109 --> 01:09:51,109
So by this analysis, having
unprotected sex.

1751
01:09:51,109 --> 01:09:53,939
Adults, bad, bad, bad.

1752
01:09:53,939 --> 01:09:54,510
OK?

1753
01:09:54,510 --> 01:09:56,280
I mean really bad.

1754
01:09:56,280 --> 01:10:00,700
Adolescents, well, let's
think about this.

1755
01:10:00,700 --> 01:10:01,350
What's the gain?

1756
01:10:01,350 --> 01:10:05,660
Well, we hear that sex is
highly pleasurable.

1757
01:10:05,660 --> 01:10:07,000
What's the loss?

1758
01:10:07,000 --> 01:10:09,120
All these things everybody's
telling us.

1759
01:10:09,120 --> 01:10:13,030
What's the odds, purely
statistically, that for a

1760
01:10:13,030 --> 01:10:17,400
single, sexual experience, you
will have the pleasure of sex,

1761
01:10:17,400 --> 01:10:20,360
but you will end up with
a terrible disease?

1762
01:10:20,360 --> 01:10:22,135
What's the odds for
one outing?

1763
01:10:24,980 --> 01:10:26,230
What do you think?

1764
01:10:28,540 --> 01:10:30,080
Here's the complexity.

1765
01:10:30,080 --> 01:10:32,450
Some people argue that
adolescents are actually more

1766
01:10:32,450 --> 01:10:34,310
accurate in their assessment
of risk, not

1767
01:10:34,310 --> 01:10:35,720
wise in their choice.

1768
01:10:35,720 --> 01:10:37,490
Do you understand the point?

1769
01:10:37,490 --> 01:10:40,280
They're actually doing the
calculations, whereas adults

1770
01:10:40,280 --> 01:10:42,170
just go, sharks bad.

1771
01:10:42,170 --> 01:10:45,690
Sexually transmitted
diseases, avoid.

1772
01:10:45,690 --> 01:10:48,450
You're not parsing through the
exact odds and circumstances,

1773
01:10:48,450 --> 01:10:51,070
the trade-offs between
exploration and pleasure and

1774
01:10:51,070 --> 01:10:52,720
responsibility and safety.

1775
01:10:52,720 --> 01:10:55,280
You just have the gist,
the line, that's it.

1776
01:10:55,280 --> 01:10:57,170
That's my wisdom that
I've gotten.

1777
01:10:57,170 --> 01:10:57,900
Sharks, bad.

1778
01:10:57,900 --> 01:10:59,720
Sexually transmitted
disease, bad.

1779
01:10:59,720 --> 01:11:01,520
That's it.

1780
01:11:01,520 --> 01:11:03,790
And these teenagers are kind
of curiously thinking about

1781
01:11:03,790 --> 01:11:04,430
what are the factors.

1782
01:11:04,430 --> 01:11:06,270
And you could say, it's
not the best analysis.

1783
01:11:06,270 --> 01:11:08,960
But you could say it's
almost more rational.

1784
01:11:08,960 --> 01:11:13,000
Just like the older adults will
make more gist errors in

1785
01:11:13,000 --> 01:11:15,600
memory, they will be more
emotional in their

1786
01:11:15,600 --> 01:11:18,130
avoidance of risk.

1787
01:11:18,130 --> 01:11:19,550
So it's very complicated.

1788
01:11:19,550 --> 01:11:21,540
It's not just dopamine
flushing.

1789
01:11:21,540 --> 01:11:22,950
It's also in the brain.

1790
01:11:22,950 --> 01:11:25,840
It's also something about how
risk is perceived at different

1791
01:11:25,840 --> 01:11:27,820
ages and what information
is available to you.

1792
01:11:27,820 --> 01:11:28,220
All right.

1793
01:11:28,220 --> 01:11:29,470
Thanks very much.