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Freeman: Our minds
store our entire lives...
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Our memories, our talents,
our deepest desires.
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Tell no one,
and our thoughts remain our own.
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But that might be
about to change.
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Our brains
are biological computers,
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vulnerable to data theft.
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Computer hackers
can read our e-mail.
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Brain hackers
may someday read our minds...
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And even rewrite our thoughts.
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Can our minds be hacked?
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Space, time, life itself.
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The secrets of the cosmos
lie through the wormhole.
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Subtital By RA_One
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we live in a world of data.
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We all know how vital it is
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to protect
our personal information,
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our passwords
and credit-card numbers,
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but what if hackers
learned to read or tamper with
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our most precious and private
store of data...
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The contents of our minds?
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Can the brain be hacked
by a computer?
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The data in our brain is not
stored as simple ones and zeros.
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Hacking into our thoughts
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requires decoding
the logic of our neurons.
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Science is getting close
to achieving that goal.
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One day soon,
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our innermost thoughts
may no longer be our own.
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I once tried to hide the truth
from my mother.
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I lied,
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but when
she looked into my eyes,
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I knew that she knew.
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How could she know?
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Man: How you doing?
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Please turn off your cellphones.
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Now put your hands together
for the one and only Marc Salem.
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Enjoy the show.
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[ Cheers and applause ]
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It's only me.
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Good evening, everybody.
I'm delighted to be here.
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What I'd like to do
is choose somebody at random...
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Freeman: Marc Salem
is one of new.
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York's most prominent
psychologists,
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but he also
has a remarkable talent,
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one that has catapulted him
into show business.
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All right,
here's what I want you to do.
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I want you to say "Stop"
At any point.
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Say "Stop" At any point.
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Woman: Stop. Okay.
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Look at the first word
on the first line.
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Have you got it? Yeah.
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Okay. Hold onto this.
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All right.
Say nothing at all to me.
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Say nothing at all to me.
Just think of the first letter.
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A, b, c, d, e, f, g, h,
I, j, k, I, m, n, o, p,
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q, r, s, t, u, v, w, x, y, z.
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Okay.
It's an "S." Is that correct?
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- Yes.
- Okay, good.
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Let's see. The second letter,
probably a vowel.
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A, e, I, o, u. A, e, I, o, u.
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- It's an "E, " Isn't it?
- Yes.
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Freeman: Marc's mind-reading
ability is not magic.
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He's reading tiny physical clues
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his subjects
are unwittingly giving him.
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Se..."E."
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- the word is "Second"?
- Yes.
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Give her a round of applause,
please.
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What I'm looking for,
first of all,
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is some kind of difference
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in the way that
they're expressing themselves.
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Should I get rid of this one
or this one?
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- That one.
- Get rid of this one.
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I think every mental thought
that we have
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has some physical
corresponding emission.
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There's something that
we can tell about that thought.
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We literally can see
people thinking.
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My friends,
let me just say once again,
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nothing that I did this evening
is supernatural.
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Nothing that I do is occult.
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Thank you so very much.
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[ Applause ]
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Freeman: From his stage shows
and from his academic research,
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Marc has learned
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that it's almost impossible
to keep a secret.
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What our brains are thinking
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can't help but leak out
into our physical bodies.
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Now, this light board is really
somewhat like your brain
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in a simplistic form.
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We have impulses traveling out
interdependently.
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That is,
each relies on the other one.
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Freeman: Just as your brain
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controls every
muscle in your body,
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our theater light board
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sends signals
to every light in the house,
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and just as the light board
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operates groups of lights
with a single command,
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so does the brain.
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For example, Clarissa,
show what would happen
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if we switched
switch number one.
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A single button triggers
a complex set of actions.
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Lights turn on.
Lights turn off.
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Others move or change color
all at once.
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In the same way,
when we think a thought,
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our brains trigger a whole set
of movements in our bodies.
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Let's say suddenly,
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it occurred to the person
that they look ridiculous.
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Hit number two, please.
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Suddenly,
that thought would change,
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and the physical
would also change.
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Perhaps a sly smile
would come on someone's face.
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Psychologists like Marc
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call these involuntary muscle
reactions information leakage.
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He believes
there's no way to stop it,
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even if you have
the perfect poker face.
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Hi, guys. I'm glad you're here.
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I know that you're,
among other things, gamblers,
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and we're gonna try
a little bit of an experiment
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with how you think
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and information
you may be giving off...
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What sometimes
you may call tells...
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What we're really looking at
as nonverbal communication.
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Could everybody
look at their card, please?
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Remember it and put it down.
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To play a game of poker,
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you need to prevent
everyone at the table
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from guessing your cards,
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but Marc believes
he can see through any player,
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no matter how blank
their expression may be.
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Let's try you.
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Think red, black.
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Focus on it.
Black, red, black, red.
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Black, black, black. Red, red.
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I think it's definitely black.
Is that correct?
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- Yes.
- Okay.
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Spades, clubs, spades, clubs.
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Okay, there's a rapid blinking,
discomfort at the spades,
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so is it a spade?
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Okay.
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Ace, 2, 3, 4, 5,
6, 7, 8, 9, 10.
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Jack, queen, king.
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There was a very tight blink
on the Jack,
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so I would think Jack.
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Salem: There are ways to know
what people are thinking.
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You have to learn
to pay attention
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to the subtle differences,
the subtle nuances,
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and that's what I do.
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I try to look
at what's normally done
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and then
what those subtle nuances are
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and plus what are universal.
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Freeman:
Natural mind readers like Marc
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can decipher thoughts from
involuntary muscle movements,
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but cutting-edge technology
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could give brain hackers
direct access to our thoughts,
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even if our muscles never move.
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Augie nieto is
a fitness industry entrepreneur.
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In 2005,
he was diagnosed with a.L.S.
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And soon became
almost completely paralyzed.
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The only parts of his body
he can move are his feet.
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He uses them
to control a speech computer.
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Even these muscles
will eventually degenerate,
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but he may not
lose the ability to communicate.
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Neurotechnology pioneer
Dr. Philip low
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is hoping to hack into augie's
mind before it's too late.
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Philip and a team of engineers
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are building
a state-of-the-art brain reader,
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a device they call the ibrain.
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I'm wearing the first portable
brain monitor ever built,
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and what it is doing is
it is recording my brain data.
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It is actually
sending it over to our servers,
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and our algorithms
can crunch it.
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Freeman: Every time we decide
to move our muscles,
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billions of neurons fire
miniature bolts of electricity
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inside our brains.
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Philip's
electrically sensitive ibrain
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can detect
these electrical pulses
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by measuring the small changes
in voltage
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they produce
on the surface of the scalp.
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By seeing the activation of
particles of brain structures,
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we can tell, "Oh, this person
is trying to move his hands."
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Freeman: Philip
thought the ibrain
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might help patients like augie
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who, despite their paralysis,
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have healthy, functioning brains
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that can still send signals
to their muscles.
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A.L.S. Patients
do not have problems
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when it comes to
their own brains.
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The areas
that his brain is using
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in order to control these limbs,
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these areas are still
working perfectly fine.
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They're just unemployed
right now.
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Hi, augie.
Nice to see you again.
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Freeman: If the ibrain
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can pick up augie's
mental intention to move,
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Philip could create a new means
for him to communicate.
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You will have a prompt.
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It will ask you to imagine to,
you know, move your right hand
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for four seconds at a time,
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and, of course, we're going to
be monitoring your brain waves
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very, very closely
during that time
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and having all of our algorithms
crunch the data
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in the background, as well.
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The test is successful.
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Philip's ibrain recognizes
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whenever augie is thinking about
moving his right or left hand.
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Low: Augie had
a very successful first test.
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We will use these brain patterns
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in order to control
a virtual hand on the screen,
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which will enable him
to just pick these words
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and pick these letters
and enable him to communicate,
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so this gives us
a lot of hope and encouragement
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that, in fact, we have a system
that will work for everybody
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and that will enable individuals
to use their brain patterns
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in order to communicate.
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Man: The biggest fear
for someone with a.L.S.
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Is to be not able
to communicate.
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That is called being locked in.
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With the ibrain, I will
never, never be locked in!
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Freeman: Soon,
augie may not even
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have to think about
moving his hand
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in order to communicate
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because a laboratory
in California
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has already begun
to translate thoughts
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into pictures and words.
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We all have thoughts
we'd rather keep to ourselves.
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When computer scientists
want to keep something secret,
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they encrypt it,
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but it's just a matter of time
before any code is cracked.
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The electrical activity buzzing
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between the neurons
in our brains
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could be
the next code we decipher.
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00:12:06,987 --> 00:12:09,822
In fact, some neuroscientists
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are already translating
the language of the brain
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into plain English.
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Neuroscientist Jack gallant
is on a mission
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to translate the flurry
of activity inside our heads
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into plain English.
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You might say
he's writing the book on it.
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Gallant: You can think
of each part of the brain
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as translating between the world
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and whatever the brain activity
is in that part of the brain,
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so there's some sort of language
you can think of
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that's gonna mediate
between the world and the brain,
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and if you had a list
of all of the things
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that related the world
to the brain,
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you would essentially
have a dictionary.
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Freeman: The first brain
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dictionary Jack set out to build
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was for the language of sight.
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There are about 50 or 70
brain areas
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that are devoted to vision,
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so there's gonna be,
essentially,
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50 or 70 different dictionaries
253
00:13:03,143 --> 00:13:04,778
that we're gonna
have to build...
254
00:13:04,779 --> 00:13:06,846
One dictionary
for each region of the brain.
255
00:13:06,847 --> 00:13:08,614
Now, that's gonna be
a really big dictionary.
256
00:13:08,615 --> 00:13:10,115
It's gonna be
much thicker than this
257
00:13:10,116 --> 00:13:12,084
because the number of things
you can see in the world
258
00:13:12,085 --> 00:13:15,356
is really, really
a large number.
259
00:13:17,558 --> 00:13:20,260
Freeman:
To build a brain dictionary,
260
00:13:20,261 --> 00:13:25,432
Jack and his colleagues
shinji nishimoto and Alex huth
261
00:13:25,433 --> 00:13:30,771
use an fmri scanner to measure
exactly how the brain responds
262
00:13:30,772 --> 00:13:33,307
to a long series of video clips.
263
00:13:35,209 --> 00:13:36,975
So, this is a viewer
that allows us
264
00:13:36,976 --> 00:13:39,380
to visualize the blood flow
while the movie plays.
265
00:13:39,381 --> 00:13:41,848
Blue means
relatively less blood flow,
266
00:13:41,849 --> 00:13:44,483
and red means
relatively more blood flow,
267
00:13:44,484 --> 00:13:45,751
and you can see
268
00:13:45,752 --> 00:13:47,821
that the blood flow's changing
quite dramatically
269
00:13:47,822 --> 00:13:50,390
as the scenes in this movie
play,
270
00:13:50,391 --> 00:13:53,960
and the problem that we have
in modeling the brain
271
00:13:53,961 --> 00:13:56,062
is to try to understand
what the relationship is
272
00:13:56,063 --> 00:14:01,401
between each individual point
in this brain and these movies.
273
00:14:01,402 --> 00:14:05,906
Freeman: But as they compiled
thousands of scans of brains
274
00:14:05,907 --> 00:14:08,141
reacting to thousands
of frames of video,
275
00:14:08,142 --> 00:14:11,611
Jack and his team found
that certain objects
276
00:14:11,612 --> 00:14:15,014
trigger predictable patterns
of blood flow,
277
00:14:15,015 --> 00:14:16,750
and they began to build
278
00:14:16,751 --> 00:14:19,586
a dictionary
of objects in the world,
279
00:14:19,587 --> 00:14:23,256
defined as particular patterns
of blood flow in the brain.
280
00:14:23,257 --> 00:14:26,125
Gallant: And then once we have
this world-brain dictionary,
281
00:14:26,126 --> 00:14:27,527
we can actually take it,
282
00:14:27,528 --> 00:14:29,696
and we can sort of
run it backwards,
283
00:14:29,697 --> 00:14:31,599
and we can create
a brain-world dictionary.
284
00:14:33,567 --> 00:14:36,169
Freeman:
To test that dictionary,
285
00:14:36,170 --> 00:14:39,572
they send their test subjects
back into the fmri
286
00:14:39,573 --> 00:14:41,107
to watch more movies,
287
00:14:41,108 --> 00:14:45,211
except this time, they don't see
what the subject sees.
288
00:14:45,212 --> 00:14:49,281
Jack and his team have to guess
using only the raw data
289
00:14:49,282 --> 00:14:54,287
from the brain scans and
an advanced computer algorithm.
290
00:14:54,288 --> 00:14:56,189
So, there are probably, say,
291
00:14:56,190 --> 00:14:58,524
10,000 points on the brain,
5,000,
292
00:14:58,525 --> 00:15:00,861
that are being used
in this model,
293
00:15:00,862 --> 00:15:05,231
and each point in the brain
has a predicted brain activity
294
00:15:05,232 --> 00:15:07,701
that it generates when you
stick an image through it,
295
00:15:07,702 --> 00:15:09,369
and then
we aggregate information
296
00:15:09,370 --> 00:15:10,770
across all those 10,000 points
297
00:15:10,771 --> 00:15:12,640
to come up
with the best prediction.
298
00:15:12,641 --> 00:15:18,211
Freeman: This is the image
that only the subject could see.
299
00:15:18,212 --> 00:15:21,548
These are the top choices
the computer selects
300
00:15:21,549 --> 00:15:23,816
from the brain-world dictionary,
301
00:15:23,817 --> 00:15:28,621
and this is
the composite average.
302
00:15:28,622 --> 00:15:32,425
No matter what the subject sees
in the world,
303
00:15:32,426 --> 00:15:37,431
the brain-world dictionary
can produce a rough copy.
304
00:15:39,600 --> 00:15:41,434
But this algorithm does more
305
00:15:41,435 --> 00:15:44,637
than just guess
what images people are watching.
306
00:15:44,638 --> 00:15:50,242
It can also guess what they are
thinking about those images.
307
00:15:50,243 --> 00:15:53,279
Here on the left is the movie
that the subjects saw,
308
00:15:53,280 --> 00:15:56,483
and on the right, you can see
2,000 nouns and verbs,
309
00:15:56,484 --> 00:15:58,785
and they change their size,
310
00:15:58,786 --> 00:16:02,021
and the size of the word
indicates the probability
311
00:16:02,022 --> 00:16:05,391
that that concept appeared
in the video at that time.
312
00:16:05,392 --> 00:16:06,695
You can see here, it
gets "Talk, "
313
00:16:06,696 --> 00:16:08,295
"Face, "
"Woman, " "Man."
314
00:16:08,296 --> 00:16:10,363
here, "Talking,
" "Man."
315
00:16:10,364 --> 00:16:14,100
you'll see, here's "Hand, "
"Room, " "Face."
316
00:16:14,101 --> 00:16:16,469
so, this is a complicated scene.
317
00:16:16,470 --> 00:16:19,639
Here we go.
We switch to an ocean scene.
318
00:16:19,640 --> 00:16:22,107
"Clouds, " "Sky, "
"Vegetation" "Waikiki, "
319
00:16:22,108 --> 00:16:23,642
"Body of water, "
"Building, "
320
00:16:23,643 --> 00:16:25,612
"Sky, " "People
walking, " "Tree."
321
00:16:25,613 --> 00:16:30,883
these are all really very
accurate semantic decodings.
322
00:16:30,884 --> 00:16:33,086
Freeman: Jack's team has built
323
00:16:33,087 --> 00:16:36,789
a dictionary of 2,000
emotionally neutral concepts
324
00:16:36,790 --> 00:16:38,324
that people might think
325
00:16:38,325 --> 00:16:40,994
when they watch
their series of videos.
326
00:16:40,995 --> 00:16:44,697
Calibrating their computers
to decode more personal meaning
327
00:16:44,698 --> 00:16:46,866
is only a matter of time
328
00:16:46,867 --> 00:16:51,537
and increasing the level
of detail in the brain scans.
329
00:16:51,538 --> 00:16:53,239
We're constantly surprised
330
00:16:53,240 --> 00:16:55,909
by how much information
we can recover,
331
00:16:55,910 --> 00:16:57,110
especially given
332
00:16:57,111 --> 00:16:58,677
that the measurements
we're taking of the brain
333
00:16:58,678 --> 00:17:00,847
are still, at this point,
really, really primitive.
334
00:17:00,848 --> 00:17:03,449
That's one thing that I think is
really exciting about this field
335
00:17:03,450 --> 00:17:04,918
and really interesting,
336
00:17:04,919 --> 00:17:07,455
and I also think
it raises a caution flag
337
00:17:07,554 --> 00:17:11,124
that I think we're gonna have to
deal with these ethical issues
338
00:17:11,125 --> 00:17:13,692
involving brain decoding
sooner rather than later,
339
00:17:13,693 --> 00:17:14,862
because we don't know
340
00:17:14,863 --> 00:17:17,063
how fast this technology's
gonna progress,
341
00:17:17,064 --> 00:17:19,398
and that opens up
a big ethical can of worms.
342
00:17:19,399 --> 00:17:21,401
You know,
when is that gonna be used?
343
00:17:21,402 --> 00:17:22,837
And what can it be used for?
344
00:17:22,838 --> 00:17:25,405
And I really think this needs
to get addressed right away.
345
00:17:25,406 --> 00:17:27,538
Freeman: Brain
hackers may soon be
346
00:17:27,539 --> 00:17:29,608
able to read your every thought.
347
00:17:29,609 --> 00:17:30,910
What then?
348
00:17:30,911 --> 00:17:35,715
If your thoughts can be decoded,
could they be altered?
349
00:17:35,716 --> 00:17:39,118
This neuroscientist
and entrepreneur
350
00:17:39,119 --> 00:17:41,387
is pushing the boundaries
of brain manipulation
351
00:17:41,388 --> 00:17:43,089
with a device
352
00:17:43,090 --> 00:17:48,129
that could turn amateurs
into experts in a single day.
353
00:17:51,969 --> 00:17:55,370
We'd all love to be truly great
at something...
354
00:17:55,371 --> 00:17:59,408
Maybe a physicist like Einstein
355
00:17:59,409 --> 00:18:02,778
or an artist like Picasso
356
00:18:02,779 --> 00:18:06,982
or a great leader
like Nelson mandela.
357
00:18:06,983 --> 00:18:08,851
Most of us have to settle
358
00:18:08,852 --> 00:18:11,821
for simply good
instead of incredible,
359
00:18:11,822 --> 00:18:17,894
but what if we could change that
by hacking our mental software
360
00:18:17,895 --> 00:18:20,529
and giving ourselves
capabilities
361
00:18:20,530 --> 00:18:23,200
we weren't born with?
362
00:18:25,435 --> 00:18:29,472
Chris berka is a neuroscientist,
engineer, inventor,
363
00:18:29,473 --> 00:18:33,876
and c.E.O.
Of a neurotech startup company.
364
00:18:33,877 --> 00:18:36,845
It's a workload
that would crush most of us,
365
00:18:36,846 --> 00:18:38,881
but she handles it
by getting into
366
00:18:38,882 --> 00:18:42,352
a high-performance,
high-output brain state.
367
00:18:42,353 --> 00:18:46,421
It's what athletes call
"The zone."
368
00:18:46,422 --> 00:18:48,090
berka: Being in the zone,
369
00:18:48,091 --> 00:18:50,760
it's essentially
just focused attention
370
00:18:50,761 --> 00:18:54,063
and the ability
to not be distracted.
371
00:18:54,064 --> 00:19:01,270
It's what allows you to really
develop perfection in any skill.
372
00:19:01,271 --> 00:19:03,490
Freeman: Getting
into the zone is
373
00:19:03,491 --> 00:19:05,708
a full-time obsession for Chris.
374
00:19:05,709 --> 00:19:08,144
Her company
is developing a device
375
00:19:08,145 --> 00:19:10,379
that she claims
can train your brain
376
00:19:10,380 --> 00:19:13,350
to work like the brain
of a highly-skilled expert.
377
00:19:27,998 --> 00:19:30,033
Chris oosterlinck
378
00:19:30,034 --> 00:19:34,170
is a California state
archery champion.
379
00:19:34,171 --> 00:19:36,238
Berka: He has a small band
around his head
380
00:19:36,239 --> 00:19:37,374
that has four sensors
381
00:19:37,375 --> 00:19:39,442
for sensing
the brain's electrical activity.
382
00:19:39,443 --> 00:19:42,111
We're gonna be looking for
the particular state
383
00:19:42,112 --> 00:19:43,278
leading up to the shot
384
00:19:43,279 --> 00:19:45,081
that we know
is the peak performance state.
385
00:19:45,082 --> 00:19:47,051
So, Chris,
do you want to get ready and go?
386
00:19:55,525 --> 00:19:59,762
Freeman: Inside Chris' brain,
billions of neurons are firing,
387
00:19:59,763 --> 00:20:01,864
creating waves of electricity.
388
00:20:01,865 --> 00:20:06,702
Different states of mind have
different frequencies of waves.
389
00:20:06,703 --> 00:20:11,207
When people are in the zone,
two frequencies dominate...
390
00:20:11,208 --> 00:20:12,508
Alpha waves,
391
00:20:12,509 --> 00:20:15,211
which indicate a state
of meditative concentration,
392
00:20:15,212 --> 00:20:17,547
like those of a zen master,
393
00:20:17,548 --> 00:20:22,852
and lower-frequency theta waves,
which show extreme relaxation.
394
00:20:22,853 --> 00:20:26,256
Berka: The red line indicates
the e.E.G. Theta activity,
395
00:20:26,257 --> 00:20:29,225
and the green line indicates
the Alpha activity,
396
00:20:29,226 --> 00:20:31,995
and we see both of those
Alpha and theta increase
397
00:20:31,996 --> 00:20:34,131
just prior
to taking the perfect shot.
398
00:20:45,944 --> 00:20:49,046
Freeman: Chris brings in
a group of amateurs.
399
00:20:49,047 --> 00:20:50,981
She wants to see
what will happen
400
00:20:50,982 --> 00:20:55,452
if she coaxes the amateurs
to take their shots
401
00:20:55,453 --> 00:20:58,656
while in the same brain state
as a professional archer.
402
00:21:02,060 --> 00:21:03,961
Berka: So, what we're doing is
403
00:21:03,962 --> 00:21:05,963
monitoring
the brain's electrical activity.
404
00:21:05,964 --> 00:21:08,799
We do that
by putting sensors on the scalp,
405
00:21:08,800 --> 00:21:10,167
and as you move through
406
00:21:10,168 --> 00:21:12,803
different cognitive states
and mental states,
407
00:21:12,804 --> 00:21:14,806
the electronic frequencies
of your brain will change,
408
00:21:14,807 --> 00:21:18,142
and we can record those
in real time and analyze them.
409
00:21:18,143 --> 00:21:22,079
Freeman: Each amateur focuses
and relaxes to reach the zone.
410
00:21:22,080 --> 00:21:25,216
Chris' monitor
records their brain waves,
411
00:21:25,217 --> 00:21:28,353
and a small haptic buzzer
on their collar
412
00:21:28,354 --> 00:21:30,288
lets them know
when they've achieved
413
00:21:30,289 --> 00:21:34,092
the same brain state
as the professional.
414
00:21:34,093 --> 00:21:37,127
We're seeing the e.E.G. Alpha
increase and theta increase.
415
00:21:37,128 --> 00:21:38,530
The haptic buzzer stopped,
416
00:21:38,531 --> 00:21:40,932
and now he's ready
to take the perfect shot.
417
00:21:40,933 --> 00:21:42,468
Go ahead, Shane.
418
00:21:50,141 --> 00:21:53,510
That was perfect. [ Chuckles ]
That was perfect.
419
00:21:53,511 --> 00:21:55,479
That's exactly the goal.
420
00:21:55,480 --> 00:21:58,182
Freeman: By the end
of only one day of practice,
421
00:21:58,183 --> 00:22:01,585
Chris' technology hacked
the minds of a group of amateurs
422
00:22:01,586 --> 00:22:07,958
to shoot at or close to a
professional level of expertise.
423
00:22:07,959 --> 00:22:10,060
Berka: And what we're able
to demonstrate
424
00:22:10,061 --> 00:22:13,163
is a 230% increase
in the speed and accuracy
425
00:22:13,164 --> 00:22:16,234
of marksmanship training.
426
00:22:17,669 --> 00:22:20,537
Freeman: Chris sees no end
of potential customers
427
00:22:20,538 --> 00:22:23,741
for her brain-hacking device...
428
00:22:23,742 --> 00:22:28,712
A corporate board that needs to
make smart group decisions,
429
00:22:28,713 --> 00:22:32,382
a president
who needs peak performance,
430
00:22:32,383 --> 00:22:35,953
or a special-forces operative
whose split-second choices
431
00:22:35,954 --> 00:22:40,090
make the difference
between life and death.
432
00:22:40,091 --> 00:22:42,994
What we're trying to do
is to give you the ability
433
00:22:42,995 --> 00:22:46,263
to control your mind
and your mental state,
434
00:22:46,264 --> 00:22:48,132
your ability to deal with
435
00:22:48,133 --> 00:22:51,102
even the most challenging
environments,
436
00:22:51,103 --> 00:22:54,838
and just by training you
to control your brain,
437
00:22:54,839 --> 00:22:58,375
you get this kind of
metacognitive awareness
438
00:22:58,376 --> 00:23:01,745
that allows you
to be much more resilient
439
00:23:01,746 --> 00:23:04,916
and adaptable
to stressful situations.
440
00:23:05,917 --> 00:23:11,687
If we can hack into our own
brains to amplify our talents,
441
00:23:11,688 --> 00:23:16,959
what's stopping us from hacking
into the brains of other people?
442
00:23:16,960 --> 00:23:21,098
Could one mind reprogram
the reality of another?
443
00:23:24,535 --> 00:23:26,803
Let's do an experiment.
444
00:23:26,804 --> 00:23:29,005
Close your eyes.
445
00:23:29,006 --> 00:23:31,307
Keep them closed.
446
00:23:31,308 --> 00:23:34,411
Now imagine you're alone
in the desert
447
00:23:34,412 --> 00:23:36,450
and your throat and mouth
are swollen with thirst.
448
00:23:38,000 --> 00:23:41,303
Now think about drinking
a cool glass of water.
449
00:23:43,471 --> 00:23:45,472
Open your eyes.
450
00:23:45,473 --> 00:23:48,142
Do you feel refreshed?
451
00:23:48,143 --> 00:23:49,543
If you do,
452
00:23:49,544 --> 00:23:55,417
I just hacked into your mind
and altered your perception.
453
00:23:58,754 --> 00:24:02,623
Stanford's David spiegel is not
your typical psychiatrist.
454
00:24:02,624 --> 00:24:05,793
He helps his patients
overcome their struggles
455
00:24:05,794 --> 00:24:07,995
through a technique
that is controversial
456
00:24:07,996 --> 00:24:10,365
for a university doctor...
457
00:24:10,366 --> 00:24:13,333
Hypnosis.
458
00:24:13,334 --> 00:24:16,503
Hypnosis is a form
of highly focused attention
459
00:24:16,504 --> 00:24:19,206
coupled with
an ability to dissociate,
460
00:24:19,207 --> 00:24:21,209
or put outside
of conscious awareness,
461
00:24:21,210 --> 00:24:23,645
things that would ordinarily
be in consciousness
462
00:24:23,646 --> 00:24:27,581
and a heightened response to
social cues or suggestibility.
463
00:24:27,582 --> 00:24:30,518
And hypnosis
is highly focused attention.
464
00:24:30,519 --> 00:24:33,489
It's been called
believed-in imagination.
465
00:24:37,692 --> 00:24:39,894
Freeman: David wanted to know
466
00:24:39,895 --> 00:24:43,564
how people perceived the world
when hypnotized,
467
00:24:43,565 --> 00:24:48,135
so he has designed an experiment
to look at the brains of people
468
00:24:48,136 --> 00:24:52,508
who have the ability
to hypnotize themselves.
469
00:24:53,608 --> 00:24:55,576
Okay, Katie,
you doing all right?
470
00:24:55,577 --> 00:24:56,778
Katie: Yep.
471
00:24:56,877 --> 00:24:58,111
- Good.
- All right, now,
472
00:24:58,812 --> 00:25:01,582
we're gonna go into
a state of self-hypnosis now.
473
00:25:01,583 --> 00:25:02,750
Uh-huh.
474
00:25:02,751 --> 00:25:05,519
So now I want your eyes
to be relaxed and closed,
475
00:25:05,520 --> 00:25:08,956
and imagine your body floating
somewhere safe and comfortable,
476
00:25:08,957 --> 00:25:12,759
like a bath, a lake, a hot tub,
or just floating in space.
477
00:25:12,760 --> 00:25:14,962
Each breath deeper and easier.
478
00:25:14,963 --> 00:25:17,698
Body floating safe
and comfortable.
479
00:25:17,699 --> 00:25:20,901
Once she is under hypnosis,
480
00:25:20,902 --> 00:25:24,204
David shows Katie
a grid of colors.
481
00:25:24,205 --> 00:25:27,242
What colors do you see now?
Just name a few.
482
00:25:33,915 --> 00:25:35,315
Good.
483
00:25:35,316 --> 00:25:38,819
Katie perceives the color grid,
484
00:25:38,820 --> 00:25:42,890
and her fusiform gyrus
lights up.
485
00:25:42,891 --> 00:25:47,962
This part of the brain becomes
active whenever we see color.
486
00:25:47,963 --> 00:25:50,865
But because
Katie's under hypnosis,
487
00:25:50,866 --> 00:25:53,902
David can now
tamper with her senses.
488
00:25:55,270 --> 00:25:57,838
And now
I want you to drain the color
489
00:25:57,839 --> 00:26:01,575
from the image in front of you
490
00:26:01,576 --> 00:26:06,380
so that what you start to see
is just gray, white, and black.
491
00:26:06,381 --> 00:26:08,517
Just drain away the color.
492
00:26:10,852 --> 00:26:14,622
Now again, remaining in this
state of concentration, Katie,
493
00:26:14,623 --> 00:26:19,228
please tell me what
the image looks like to you now.
494
00:26:30,538 --> 00:26:32,306
- Good.
- Yeah.
495
00:26:32,307 --> 00:26:36,677
Physically,
the color image has not changed,
496
00:26:36,678 --> 00:26:43,116
but David now takes another scan
of Katie's fusiform gyrus.
497
00:26:43,117 --> 00:26:44,419
Spiegel: So, we're looking now
498
00:26:44,420 --> 00:26:45,720
at the regions of the brain
499
00:26:45,721 --> 00:26:47,487
that actually light up,
500
00:26:47,488 --> 00:26:50,258
because there's more blood flow
when they're looking at color
501
00:26:50,259 --> 00:26:52,392
than when they're looking
at black and white.
502
00:26:52,393 --> 00:26:54,228
Here is what the blood flow was
503
00:26:54,229 --> 00:26:56,697
when they were
really looking at color,
504
00:26:56,698 --> 00:26:59,101
and here's the blood flow
when they were looking at color
505
00:26:59,102 --> 00:27:02,002
but drained it of color
and saw it as black and white.
506
00:27:02,003 --> 00:27:06,006
Freeman: Even though she's still
looking at a color image,
507
00:27:06,007 --> 00:27:10,477
the blood flow to Katie's
fusiform gyrus is decreasing.
508
00:27:10,478 --> 00:27:12,880
It is proof that her brain
509
00:27:12,881 --> 00:27:16,316
is turning off her ability
to see color
510
00:27:16,317 --> 00:27:18,685
at David's suggestion.
511
00:27:18,686 --> 00:27:22,159
The image she perceives
is becoming black and white.
512
00:27:24,860 --> 00:27:27,830
David believes that
hypnosis opened up Katie's brain
513
00:27:27,831 --> 00:27:28,931
for reprogramming.
514
00:27:29,000 --> 00:27:31,502
His thoughts
hacked into her mind
515
00:27:31,503 --> 00:27:36,173
and became
her real living experience.
516
00:27:36,174 --> 00:27:40,211
We tend to think that the brain
processes raw information
517
00:27:40,212 --> 00:27:42,879
and we make sense of it
afterwards,
518
00:27:42,880 --> 00:27:44,247
but it turns out,
519
00:27:44,248 --> 00:27:46,951
especially
in studies of hypnosis,
520
00:27:46,952 --> 00:27:48,417
that we can reset the brain,
521
00:27:48,418 --> 00:27:49,821
that we can change the way
522
00:27:49,822 --> 00:27:52,055
the brain
actually perceives information,
523
00:27:52,056 --> 00:27:54,992
so it's not that it reacts
differently to the same input.
524
00:27:54,993 --> 00:27:57,494
It changes what the input is.
525
00:27:57,495 --> 00:28:01,898
Freeman: David's work suggests
that while under hypnosis,
526
00:28:01,899 --> 00:28:06,404
the way our brains
perceive reality is altered.
527
00:28:07,705 --> 00:28:11,542
I had a student who was doing
research with me on hypnosis
528
00:28:11,543 --> 00:28:15,479
who is also a really talented
athlete for the football team.
529
00:28:15,480 --> 00:28:18,749
He was terrific,
and he was very hypnotizable,
530
00:28:18,750 --> 00:28:20,083
and I would say to him,
531
00:28:20,084 --> 00:28:22,554
"So, what's going on
when you're playing like this?"
532
00:28:22,555 --> 00:28:25,021
he said, "Doc,
when I'm having a good day,
533
00:28:25,022 --> 00:28:26,690
I'm aware of two things.
534
00:28:26,691 --> 00:28:29,760
I'm aware of the football
and the defender."
535
00:28:29,761 --> 00:28:31,328
[ crowd cheering ]
536
00:28:31,329 --> 00:28:33,964
And he said, "And there's
20 other big guys on the field.
537
00:28:33,965 --> 00:28:35,297
I don't know they're there.
538
00:28:35,298 --> 00:28:37,702
There's 60,000 people
yelling at me from the stands.
539
00:28:37,703 --> 00:28:39,336
I don't hear them."
540
00:28:39,337 --> 00:28:42,372
clearly, our minds
are programmable.
541
00:28:42,373 --> 00:28:45,308
We have hardware that allows us
to take in input, process it,
542
00:28:45,309 --> 00:28:46,545
and do something with it,
543
00:28:46,546 --> 00:28:48,778
and that input
can come from ourself
544
00:28:48,779 --> 00:28:50,748
or from people around us.
545
00:28:50,749 --> 00:28:56,620
Freeman: Hypnotism opens
our minds to brain hackers,
546
00:28:56,621 --> 00:28:58,822
but we have to make
a conscious choice
547
00:28:58,823 --> 00:29:00,258
to enter a hypnotic state,
548
00:29:00,259 --> 00:29:03,460
like a computer
that can accept or reject
549
00:29:03,461 --> 00:29:05,296
another user logging on.
550
00:29:06,029 --> 00:29:11,366
There may be a hole in our
neurological security, however.
551
00:29:11,367 --> 00:29:14,469
A team of researchers
in Tel Aviv
552
00:29:14,470 --> 00:29:16,738
claims to have found an exploit
553
00:29:16,739 --> 00:29:20,309
that could open
our unconscious mind to hackers.
554
00:29:22,000 --> 00:29:25,436
Freeman:
Think back to your childhood.
555
00:29:25,437 --> 00:29:27,204
What do you recall?
556
00:29:27,205 --> 00:29:30,008
Your mother's perfume?
557
00:29:30,009 --> 00:29:32,210
Fresh-cut grass?
558
00:29:32,211 --> 00:29:35,179
Oatmeal cookies
baking in the oven?
559
00:29:35,180 --> 00:29:38,115
A familiar scent
can flood the mind
560
00:29:38,116 --> 00:29:41,686
with images, memories,
and emotions
561
00:29:41,687 --> 00:29:44,789
whether we like it or not.
562
00:29:44,790 --> 00:29:48,393
Computer hackers write programs
called cracks
563
00:29:48,394 --> 00:29:51,328
to break into secure systems.
564
00:29:51,329 --> 00:29:56,802
Could your sense of smell
be a crack for a brain hacker?
565
00:30:04,810 --> 00:30:08,045
Ilana hairston
is a research psychologist
566
00:30:08,046 --> 00:30:09,647
in Tel Aviv, Israel.
567
00:30:09,648 --> 00:30:13,651
Ilana is fascinated
by what happens in our brains
568
00:30:13,652 --> 00:30:15,453
when we sleep.
569
00:30:15,454 --> 00:30:20,525
It began with an experiment
she did in her student days.
570
00:30:20,526 --> 00:30:22,561
Hairston: At the time,
I was working with animals,
571
00:30:22,562 --> 00:30:25,129
and I could see that
I would train animals on a maze
572
00:30:25,130 --> 00:30:27,899
and they would not learn.
573
00:30:27,900 --> 00:30:30,002
"Clearly, " I thought,
"These animals are very stupid, "
574
00:30:30,003 --> 00:30:32,002
and then I'd go back,
put them in the cage,
575
00:30:32,003 --> 00:30:34,005
come back the next day,
and boom,
576
00:30:34,006 --> 00:30:37,007
they performed like they'd been
practicing the whole night,
577
00:30:37,008 --> 00:30:38,776
and it just blew my mind.
578
00:30:38,777 --> 00:30:42,580
It made me realize we spend
a third of our life asleep,
579
00:30:42,581 --> 00:30:45,716
and there's so much going on
while we sleep.
580
00:30:45,717 --> 00:30:47,553
Freeman: Ilana thinks that our
581
00:30:47,554 --> 00:30:49,387
minds must be able to learn
582
00:30:49,388 --> 00:30:51,055
when we lose consciousness.
583
00:30:51,056 --> 00:30:56,795
To prove it, she's plotting
to break into the sleeping mind.
584
00:30:56,796 --> 00:30:59,998
It's a job that requires her
to first get past
585
00:30:59,999 --> 00:31:03,768
the brain's night watchman,
the thalamus.
586
00:31:03,769 --> 00:31:06,171
Hairston: There's a part of
the brain called the thalamus.
587
00:31:06,172 --> 00:31:07,705
What it typically does,
588
00:31:07,706 --> 00:31:10,341
it's gonna clamp down
on sensory information
589
00:31:10,342 --> 00:31:12,009
and stop you from waking up,
590
00:31:12,010 --> 00:31:15,046
or if it says, "Okay,
this is important information.
591
00:31:15,047 --> 00:31:17,949
You need to wake up, "
It'll cause you to wake up.
592
00:31:17,950 --> 00:31:19,940
Freeman: But Ilana
believes there
593
00:31:19,941 --> 00:31:21,753
is a back door into the brain
594
00:31:21,754 --> 00:31:23,754
when we sleep...
595
00:31:23,755 --> 00:31:26,157
Our sense of smell.
596
00:31:26,158 --> 00:31:29,195
Smell goes first
to the cortex...
597
00:31:30,929 --> 00:31:34,132
And so it kind of bypasses
this relay station.
598
00:31:34,133 --> 00:31:37,035
Basically, you can
enter the sleeping brain
599
00:31:37,036 --> 00:31:39,270
without going through
this relay station.
600
00:31:39,271 --> 00:31:41,439
Freeman: When we fall asleep,
601
00:31:41,440 --> 00:31:44,576
the thalamus
acts like a watchful nanny.
602
00:31:44,577 --> 00:31:48,446
Our senses try to deliver
information to the brain
603
00:31:48,447 --> 00:31:50,081
but are turned away.
604
00:31:50,082 --> 00:31:53,518
Input from our sense of smell,
however,
605
00:31:53,519 --> 00:31:55,987
has direct access,
606
00:31:55,988 --> 00:31:57,488
and once inside,
607
00:31:57,489 --> 00:32:00,792
sensory signals
that are normally tuned out
608
00:32:00,793 --> 00:32:02,660
during our sleep
609
00:32:02,661 --> 00:32:04,563
can be snuck in.
610
00:32:06,398 --> 00:32:08,732
Ilana teamed up
with research partners
611
00:32:08,733 --> 00:32:11,035
at the weizmann institute
612
00:32:11,036 --> 00:32:14,105
to hack into the minds
of sleeping test subjects
613
00:32:14,106 --> 00:32:15,973
using odors.
614
00:32:15,974 --> 00:32:18,710
They hook a test subject up
to a machine
615
00:32:18,711 --> 00:32:22,646
that can produce
a wide variety of sense
616
00:32:22,647 --> 00:32:26,352
and then measure
how deeply the subject breathes.
617
00:32:28,788 --> 00:32:32,356
The subject falls
into a deep sleep,
618
00:32:32,357 --> 00:32:36,227
and Ilana and her colleague
go to work.
619
00:32:36,228 --> 00:32:39,063
They release a pleasant perfume
620
00:32:39,064 --> 00:32:42,901
and immediately play
a high-pitched tone.
621
00:32:42,902 --> 00:32:44,470
[ High-pitched tone plays ]
622
00:32:46,872 --> 00:32:50,142
Later, they release the smell
of rotting fish...
623
00:32:53,612 --> 00:32:56,113
And play a low-pitched tone.
624
00:32:56,114 --> 00:32:58,750
[ Low-pitched tone plays ]
625
00:32:58,751 --> 00:33:03,789
The process repeats throughout
the night until morning arrives.
626
00:33:09,428 --> 00:33:13,998
Hairston: So, we just got
our participant out of bed,
627
00:33:13,999 --> 00:33:16,000
and he's not hearing or smelling
anything,
628
00:33:16,001 --> 00:33:19,571
and we're gonna present the
tones alone without the smells
629
00:33:19,572 --> 00:33:21,940
to see if he responds
to the tones.
630
00:33:21,941 --> 00:33:24,775
So, now we're just
watching him breathing.
631
00:33:24,776 --> 00:33:27,912
Freeman: The subject
had no conscious awareness
632
00:33:27,913 --> 00:33:30,414
of the odors presented
throughout the night
633
00:33:30,415 --> 00:33:32,916
and has no memory of them now,
634
00:33:32,917 --> 00:33:34,485
but Ilana wants to see
635
00:33:34,486 --> 00:33:36,653
if his breathing patterns reveal
636
00:33:36,654 --> 00:33:39,757
an unconscious,
visceral reaction
637
00:33:39,758 --> 00:33:42,560
to the high and low tones.
638
00:33:42,561 --> 00:33:45,630
She first plays the tone
linked to the perfume.
639
00:33:45,631 --> 00:33:47,398
[ High-pitched tone plays ]
640
00:33:47,399 --> 00:33:50,501
The inhale
was much bigger and wider
641
00:33:50,502 --> 00:33:54,104
compared to his normal inhales.
642
00:33:54,105 --> 00:33:56,708
We paired this tone
with a pleasant odor.
643
00:33:56,709 --> 00:33:59,276
Then she plays
the low-pitched tone,
644
00:33:59,277 --> 00:34:02,379
the one that was paired
with the foul stench.
645
00:34:02,380 --> 00:34:04,749
[ Low-pitched tone plays ]
646
00:34:04,750 --> 00:34:07,785
Again, you can see
the trigger of the tone,
647
00:34:07,786 --> 00:34:09,821
and he's literally
holding his breath.
648
00:34:09,822 --> 00:34:12,823
The subject
does not smell anything,
649
00:34:12,824 --> 00:34:16,794
but his mind reacts
as though he does.
650
00:34:16,795 --> 00:34:19,497
He associates
the high-pitched tone
651
00:34:19,498 --> 00:34:22,434
with pleasant, breathable air
652
00:34:22,533 --> 00:34:27,705
and the low-pitched tone
with foul, nauseating odors.
653
00:34:27,806 --> 00:34:28,972
The key issue here
654
00:34:28,973 --> 00:34:30,842
is also that he doesn't
actually remember anything
655
00:34:30,843 --> 00:34:32,343
that happened during the night.
656
00:34:32,344 --> 00:34:35,113
He's not actually aware
that this tone was associated
657
00:34:35,114 --> 00:34:36,981
with a bad smell
or a good smell.
658
00:34:36,982 --> 00:34:39,284
He's just responding
to the tone
659
00:34:39,285 --> 00:34:42,587
without any knowledge
of what we expect him to do.
660
00:34:42,588 --> 00:34:46,424
Ilana believes that
this brain-hacking technique
661
00:34:46,425 --> 00:34:52,797
can be refined and used to
manipulate any unconscious mind.
662
00:34:52,798 --> 00:34:54,500
Hairston:
And then the question is
663
00:34:54,501 --> 00:34:57,268
can we do this
with a more subtle paradigm,
664
00:34:57,269 --> 00:34:59,035
like training people
during sleep?
665
00:34:59,036 --> 00:35:00,939
And I think the answer
would be "Yes."
666
00:35:00,940 --> 00:35:05,076
Freeman:
Take, for example, politics.
667
00:35:05,077 --> 00:35:08,112
Your support of one candidate
668
00:35:08,113 --> 00:35:11,282
might seem, to you,
to be unswervable.
669
00:35:11,283 --> 00:35:15,153
But while you are sleeping,
670
00:35:15,154 --> 00:35:17,755
scent hackers
could train your mind
671
00:35:17,756 --> 00:35:20,391
to associate
pleasant or foul odors
672
00:35:20,392 --> 00:35:22,960
with just about any sound,
673
00:35:22,961 --> 00:35:28,632
even the sound
of a particular person's voice.
674
00:35:28,633 --> 00:35:31,101
The next time
you hear that voice,
675
00:35:31,102 --> 00:35:33,938
your newly-learned
subconscious reaction
676
00:35:33,939 --> 00:35:37,843
could turn adulation
into disgust.
677
00:35:42,380 --> 00:35:44,749
Hairston:
Because odors are emotional,
678
00:35:44,750 --> 00:35:48,352
I think we could modify our
emotional responses to stimuli,
679
00:35:48,353 --> 00:35:50,922
so I think you could
modify emotional responses
680
00:35:50,923 --> 00:35:53,090
and thereby modify behavior.
681
00:35:53,091 --> 00:35:55,893
Freeman: Someday,
682
00:35:55,894 --> 00:35:59,897
how we react to anything
in the world around us
683
00:35:59,898 --> 00:36:04,201
could be manipulated
by a brain hacker.
684
00:36:04,202 --> 00:36:08,005
It's a future that may come
sooner than you think,
685
00:36:08,006 --> 00:36:10,441
because this scientist
686
00:36:10,442 --> 00:36:14,345
is already building
the ultimate brain hack.
687
00:36:14,346 --> 00:36:18,115
His technology could
put any thought into our heads
688
00:36:18,116 --> 00:36:20,919
with a flash of light.
689
00:36:23,000 --> 00:36:25,668
Today,
we can manipulate human brains
690
00:36:25,669 --> 00:36:29,706
by tampering with the senses,
bathing the brain in chemicals,
691
00:36:29,707 --> 00:36:33,576
or by playing
psychological mind games.
692
00:36:33,577 --> 00:36:38,815
But all these methods influence
the brain from the outside in.
693
00:36:38,816 --> 00:36:40,450
A true mind hack,
694
00:36:40,451 --> 00:36:44,621
one that opens us up
for reprogramming of any kind,
695
00:36:44,622 --> 00:36:48,557
may require something
more audacious...
696
00:36:48,558 --> 00:36:54,364
Reaching inside a living brain
and flicking a switch.
697
00:36:58,302 --> 00:37:03,306
M.I.T. Engineer, physicist,
and neuroscientist ed boyden
698
00:37:03,307 --> 00:37:07,877
has spent his career figuring
out how complex machines work.
699
00:37:07,878 --> 00:37:12,082
He's now working on the
most complex machine of all...
700
00:37:12,083 --> 00:37:15,351
The human brain.
701
00:37:15,352 --> 00:37:18,888
A cubic millimeter of
brain tissue has 100,000 cells,
702
00:37:18,889 --> 00:37:21,391
and there are a billion
connections between them.
703
00:37:21,392 --> 00:37:23,392
These cells compute
using electricity,
704
00:37:23,393 --> 00:37:25,661
and if all these
little electrical computers
705
00:37:25,662 --> 00:37:28,197
could be recorded, perturbed,
controlled, and analyzed,
706
00:37:28,198 --> 00:37:30,733
then maybe we could understand
how the brain computed it
707
00:37:30,734 --> 00:37:32,268
in the same way that computers
708
00:37:32,269 --> 00:37:34,370
are engineered to do
all the things that they do
709
00:37:34,371 --> 00:37:36,506
and our phones
and on the Internet and so on.
710
00:37:36,507 --> 00:37:38,074
So,
if you have a complex system,
711
00:37:38,075 --> 00:37:41,110
whether it's a computer or a
city or the economy or a brain,
712
00:37:41,111 --> 00:37:43,913
one of the ways that you
can figure out what's going on
713
00:37:43,914 --> 00:37:45,282
is to actually put
little inputs into the system
714
00:37:45,283 --> 00:37:46,882
and see what happens.
715
00:37:46,883 --> 00:37:48,718
Freeman: It's easy to test the
716
00:37:48,719 --> 00:37:51,287
components on a
computer circuit board,
717
00:37:51,288 --> 00:37:53,756
but brain cells
are a little trickier,
718
00:37:53,757 --> 00:37:57,493
so ed set out
to find a natural switch
719
00:37:57,494 --> 00:38:01,598
that can turn individual neurons
on or off,
720
00:38:01,599 --> 00:38:07,170
and he found one swimming around
in a puddle of pond water.
721
00:38:07,171 --> 00:38:10,206
Boyden: This kind of algae
actually has this light sensor.
722
00:38:10,207 --> 00:38:12,373
It sits in a little eye spot
in the back of the algae,
723
00:38:12,374 --> 00:38:14,610
and basically, these are
little light-activated proteins
724
00:38:14,611 --> 00:38:15,846
known as opsins
725
00:38:15,847 --> 00:38:17,914
that sit
in the membranes of cells
726
00:38:17,915 --> 00:38:20,884
and serve as photosynthetic
or photosensory protein,
727
00:38:20,885 --> 00:38:23,653
and this is a molecule
that converts light
728
00:38:23,654 --> 00:38:26,323
into a very specific change
in electrical potential,
729
00:38:26,324 --> 00:38:29,392
the exact same kind that occurs
in neurons when they're active.
730
00:38:29,393 --> 00:38:33,096
Freeman: Ed and his colleagues
extracted from the algae
731
00:38:33,097 --> 00:38:37,867
the genetic code that produces
these light-sensitive opsins.
732
00:38:37,868 --> 00:38:41,304
They then inserted this gene
into a virus
733
00:38:41,305 --> 00:38:47,210
that could splice itself into
the DNA of living brain cells.
734
00:38:47,211 --> 00:38:50,146
Boyden: The neurons in the brain
will manufacture the protein
735
00:38:50,147 --> 00:38:52,348
because now the genome
has been incorporated
736
00:38:52,349 --> 00:38:53,850
into the nucleus of other cells
737
00:38:53,851 --> 00:38:56,020
and then expressed those
proteins all over the membranes,
738
00:38:56,021 --> 00:38:58,287
or boundaries, of those cells.
739
00:38:58,288 --> 00:39:01,424
Freeman: Ed's virus
instructs any infected neurons
740
00:39:01,425 --> 00:39:05,161
to build
a light-sensitive on/off switch.
741
00:39:05,162 --> 00:39:07,997
With these switches,
any brain circuit
742
00:39:07,998 --> 00:39:11,601
from our senses to
our emotional state and memories
743
00:39:11,602 --> 00:39:14,336
could be controlled with this.
744
00:39:14,337 --> 00:39:17,640
Boyden: So, this is a laser
that we developed here,
745
00:39:17,641 --> 00:39:19,541
which will then
split that laser light
746
00:39:19,542 --> 00:39:21,345
out into an array
of optical fibers
747
00:39:21,346 --> 00:39:23,479
that we can enter information
into the brain
748
00:39:23,480 --> 00:39:25,047
into many different points
749
00:39:25,048 --> 00:39:28,151
that are distributed
in a three-dimensional pattern.
750
00:39:28,152 --> 00:39:29,652
The brain doesn't feel pain,
751
00:39:29,653 --> 00:39:32,222
so we can implant little probes
into the brain,
752
00:39:32,223 --> 00:39:34,557
deliver light
out the end of these probes,
753
00:39:34,558 --> 00:39:37,060
and then we'll turn on or off
parts of the brain
754
00:39:37,061 --> 00:39:38,496
just by pulsing this laser,
755
00:39:38,497 --> 00:39:40,731
turning the laser on and off
very rapidly.
756
00:39:42,666 --> 00:39:44,234
Freeman: Ed and his colleagues
757
00:39:44,235 --> 00:39:45,967
first put that technology
to trial
758
00:39:45,968 --> 00:39:47,003
with animal subjects.
759
00:39:47,004 --> 00:39:50,372
Ed wired
his light-sensitive switches
760
00:39:50,373 --> 00:39:55,044
into a mouse's
pleasure-reward brain circuits.
761
00:39:55,045 --> 00:39:57,313
We put in an optical fiber
into the brain
762
00:39:57,314 --> 00:39:59,883
such that it could deliver light
to those cells.
763
00:39:59,884 --> 00:40:01,784
Then we programmed a computer
such that
764
00:40:01,785 --> 00:40:04,287
whenever a mouse hooked its nose
into a little sensor,
765
00:40:04,288 --> 00:40:05,921
it would get a pulse of light.
766
00:40:05,922 --> 00:40:07,857
Freeman:
Each pulse of blue light
767
00:40:07,858 --> 00:40:10,292
activates the same
pleasure-reward circuits
768
00:40:10,293 --> 00:40:12,996
that turn on when
the rodent eats a piece of food
769
00:40:12,997 --> 00:40:14,730
or finds a mate.
770
00:40:14,731 --> 00:40:18,033
The mouse keeps poking its head
into the hole,
771
00:40:18,034 --> 00:40:20,570
convinced
that this simple action
772
00:40:20,571 --> 00:40:24,140
is the source of the reward.
773
00:40:24,141 --> 00:40:25,942
Boyden: And so, what we found
774
00:40:25,943 --> 00:40:28,778
was that mice would actually
work for light.
775
00:40:28,779 --> 00:40:30,913
They would poke their nose
in the little sensor,
776
00:40:30,914 --> 00:40:33,248
get a pulse of light, say,
"Hey, that was interesting, "
777
00:40:33,249 --> 00:40:35,051
and then do it
over and over again,
778
00:40:35,052 --> 00:40:37,721
basically doing a task in order
to get a pulse of light.
779
00:40:37,722 --> 00:40:39,688
And so what this tells us is
780
00:40:39,689 --> 00:40:42,358
that very brief activation
of this set of cells
781
00:40:42,359 --> 00:40:43,792
with a pulse of light
782
00:40:43,793 --> 00:40:46,429
is enough to reinforce
whatever the animal was doing
783
00:40:46,430 --> 00:40:47,597
just before.
784
00:40:47,598 --> 00:40:51,200
Freeman: Ed has
hacked the mind of a mouse
785
00:40:51,201 --> 00:40:53,303
and changed its behavior,
786
00:40:53,304 --> 00:40:56,572
and he believes it won't be long
787
00:40:56,573 --> 00:41:00,577
before we are ready to use the
technique on the human brain.
788
00:41:00,578 --> 00:41:03,045
Boyden: Arguably, humans
have been hacking the brain
789
00:41:03,046 --> 00:41:04,479
for a very long time, you know.
790
00:41:04,480 --> 00:41:05,582
Beer, coffee...
791
00:41:05,583 --> 00:41:07,850
Those are examples
of neurotechnologies
792
00:41:07,851 --> 00:41:10,986
that their main role is
to change what the brain does.
793
00:41:10,987 --> 00:41:13,556
Drugs, pharmaceuticals
have been very, very impactful
794
00:41:13,557 --> 00:41:15,225
in treating brain disorders,
795
00:41:15,226 --> 00:41:17,226
but if you think about the brain
as a circuit,
796
00:41:17,227 --> 00:41:19,394
then a drug that goes throughout
the entire brain
797
00:41:19,395 --> 00:41:21,832
is gonna affect circuits
that you want to leave intact,
798
00:41:21,833 --> 00:41:23,899
as well as circuits
that you want to fix,
799
00:41:23,900 --> 00:41:26,669
and that's where
our technologies come into play.
800
00:41:26,670 --> 00:41:29,072
We really can make
a subset of those cells
801
00:41:29,073 --> 00:41:31,475
activatable or silenceable
with our tools.
802
00:41:33,210 --> 00:41:35,320
Freeman: Ed's
technology could be a
803
00:41:35,321 --> 00:41:37,547
cure for the nearly
1 billion people
804
00:41:37,548 --> 00:41:39,883
who suffer from mental illness
805
00:41:39,884 --> 00:41:43,452
by turning off
only unhealthy cells.
806
00:41:43,453 --> 00:41:48,024
It would be a revolution
in psychiatric medicine,
807
00:41:48,025 --> 00:41:50,827
and one day,
it could give us all
808
00:41:50,828 --> 00:41:56,332
complete control
of the workings of our brains.
809
00:41:56,333 --> 00:42:01,805
The rewards for hacking into
our brains could be momentous.
810
00:42:01,806 --> 00:42:05,407
Mental diseases
could be eliminated.
811
00:42:05,408 --> 00:42:09,044
We could unlock
the highest levels of talent,
812
00:42:09,045 --> 00:42:13,415
and we could truly understand
what another person feels.
813
00:42:13,416 --> 00:42:17,553
But there is a dark side
to this technology.
814
00:42:17,554 --> 00:42:19,922
We could be creating a future
815
00:42:19,923 --> 00:42:23,159
where no one
is sure of who they are,
816
00:42:23,160 --> 00:42:26,329
no secrets could ever be safe,
817
00:42:26,330 --> 00:42:31,835
and where we might all
lose our minds to brain hackers.
65325
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