< Return to Video

Mind reading with brain scanners | John-Dylan Hayes | TEDxBerlin

  • 0:08 - 0:12
    OK, so it's time
    to let your trousers down.
  • 0:12 - 0:15
    Let's face it, we all have
    a couple of secrets, yeah?
  • 0:16 - 0:17
    Everyone has a secret,
  • 0:17 - 0:22
    and I'd like to invite you to participate
    in a simple experiment right now.
  • 0:22 - 0:24
    I'd like you to think one of your secrets.
  • 0:24 - 0:28
    Just think it by conjuring up
    the image in your mind.
  • 0:28 - 0:32
    We tend to think these secrets are secret;
    nobody knows about them.
  • 0:32 - 0:34
    You would think because it's in your mind
  • 0:34 - 0:37
    it doesn't mean
    your neighbor sitting next you
  • 0:37 - 0:39
    can understand
    or know about your secret.
  • 0:39 - 0:41
    That's why I want to challenge here.
  • 0:41 - 0:45
    I want to ask you about
    whether your privacy is real,
  • 0:45 - 0:47
    the way you feel it.
  • 0:47 - 0:50
    Now your secret might
    be something mundane.
  • 0:50 - 0:53
    It might be something simple such as,
    for example, the PIN of your credit card.
  • 0:53 - 0:56
    It could be something embarrassing
    you don't want people to know,
  • 0:56 - 1:01
    for example, it could be you enjoy
    watching funny cat movies on the Internet,
  • 1:01 - 1:03
    something like that.
  • 1:03 - 1:05
    So, is it possible
    to read out these thoughts?
  • 1:07 - 1:12
    In fact, we can tell about the person's
    mental state to some degree
  • 1:12 - 1:15
    about their feelings
    from their body language,
  • 1:15 - 1:18
    from the expressions on their faces.
  • 1:18 - 1:21
    If you look at these
    famous Ekman faces here,
  • 1:21 - 1:25
    you can see that our facial expressions
    give away what we feel,
  • 1:25 - 1:28
    but this is still severely limited.
  • 1:28 - 1:32
    If you look at the person on the left,
    obviously she is surprised.
  • 1:32 - 1:35
    But what is she surprised about?
    What is she looking at?
  • 1:35 - 1:38
    What is she hearing?
    What is surprising her? We don't know.
  • 1:38 - 1:41
    We can't tell this
    from the surface of the body,
  • 1:41 - 1:45
    from the body language or from face;
    we somehow need to go deeper.
  • 1:45 - 1:48
    And deeper here means
    that we need to go into that part
  • 1:48 - 1:52
    of the body that encodes
    and stores your thoughts,
  • 1:52 - 1:54
    and that is the human brain.
  • 1:54 - 1:58
    Now, I am a brain scientist,
    and for many years brain scientists
  • 1:58 - 2:01
    have established fact after fact
    about the brain.
  • 2:01 - 2:02
    One thing that's always shown up
  • 2:02 - 2:07
    is that our thoughts are intimately
    related to the brain processes.
  • 2:07 - 2:11
    So, it should in theory be possible -
    if I put someone in a brain scanner -
  • 2:11 - 2:13
    to find out what they are thinking.
  • 2:13 - 2:18
    The question though is: How do I know
    to interpret the language of the brain?
  • 2:18 - 2:22
    I somehow need to translate it
    when I want to read it out.
  • 2:22 - 2:25
    I need some understanding
    of the way information is stored.
  • 2:25 - 2:29
    So, a simple analogy can help us here.
  • 2:29 - 2:31
    We could think of the way
    in which information is stored
  • 2:31 - 2:34
    on the surface of a CD.
    How does this work?
  • 2:34 - 2:39
    It's the pattern of pits on the surface
    of a CD that codes a piece of information,
  • 2:39 - 2:41
    say, for example, about a piece of music:
  • 2:41 - 2:44
    One piece of music,
    one pattern of surface;
  • 2:44 - 2:48
    a different piece of music,
    a different pattern of surface.
  • 2:48 - 2:51
    This is very similar to the way
    your brain stores information.
  • 2:51 - 2:56
    It stores your thoughts
    in spatial patterns of the brain activity.
  • 2:56 - 2:58
    So, how can we read these out?
  • 2:58 - 3:01
    How do we know what the spatial patterns
    of the brain activity are?
  • 3:01 - 3:04
    For this we use so-called brain scanners.
  • 3:04 - 3:08
    It's a technology known as MRI,
    Magnetic Resonance Imaging,
  • 3:08 - 3:11
    and basically involves
    very strong magnetic fields.
  • 3:11 - 3:13
    It doesn't do you any harm,
  • 3:13 - 3:17
    but it gives you a quite well resolved map
    of your brain activity.
  • 3:17 - 3:18
    So, that's what we do.
  • 3:18 - 3:22
    My job is people come to my lab,
    at the Charité here in Berlin,
  • 3:22 - 3:24
    and we put people in brain scanners,
  • 3:24 - 3:27
    we read out the brain activity patterns,
  • 3:27 - 3:31
    and now we get something
    that looks like this.
  • 3:31 - 3:33
    A brain image.
  • 3:33 - 3:35
    Don't confuse these brain images
    with photographs.
  • 3:35 - 3:37
    They are not photographs.
  • 3:37 - 3:42
    They are not like accurate, perfect
    depictions of some spatial events.
  • 3:42 - 3:46
    What they show is a spatial map
    of probability
  • 3:46 - 3:50
    that tells you most likely
    this part of the brain is involved
  • 3:50 - 3:52
    in some kinds of thought.
  • 3:52 - 3:56
    You can see some regions
    are hot colored, red or orange;
  • 3:56 - 3:59
    they are the regions that become
    more active than usual
  • 3:59 - 4:00
    when you engage in a specific thought.
  • 4:00 - 4:06
    The cold areas, blue areas are
    where the activity is lower than normal.
  • 4:06 - 4:10
    But what does this specific pattern
    of the brain activity mean?
  • 4:10 - 4:13
    Does anyone know what this person
    is currently thinking about?
  • 4:13 - 4:14
    What do you think?
  • 4:14 - 4:16
    It's difficult.
  • 4:16 - 4:19
    It doesn't say on there
    this person is thinking
  • 4:19 - 4:22
    about the Brandenburg Gate
    or something like that.
  • 4:22 - 4:24
    It's not written in there.
  • 4:24 - 4:27
    Instead it's an abstract code
    that the brain uses.
  • 4:27 - 4:30
    This is something
    that's quite familiar to us.
  • 4:30 - 4:31
    We know this.
  • 4:31 - 4:34
    People faced this problem
    over 200 years ago;
  • 4:34 - 4:37
    in fact, when they
    encountered the hieroglyphs.
  • 4:37 - 4:39
    People 200 years ago
    were puzzled by hieroglyphs;
  • 4:39 - 4:42
    they didn't know what hieroglyphs mean.
  • 4:42 - 4:43
    They saw this on the pyramids.
  • 4:43 - 4:46
    Some people must have said,
    "That must be like a pretty wallpaper.
  • 4:46 - 4:50
    But instead, others might have said,
    "I think it actually means something."
  • 4:50 - 4:52
    But what does it mean?
  • 4:52 - 4:55
    What do you think this means?
    It's a very similar problem.
  • 4:55 - 4:58
    What does this mean?
    Like the brain image, you can't know.
  • 4:58 - 5:03
    I can tell you this one here means
    the brain as you might have guessed.
  • 5:03 - 5:05
    But how do you know this?
  • 5:05 - 5:09
    I don't have any ancient Egyptians
    in my family. How do I know this?
  • 5:09 - 5:12
    It's because people
    stumbled on the translation.
  • 5:12 - 5:17
    In 1799, someone found the translation,
    the famous Rosetta Stone,
  • 5:17 - 5:20
    that you can see
    in the British Museum in London.
  • 5:20 - 5:26
    This famous Rosetta Stone
    contains a text in hieroglyphs
  • 5:26 - 5:29
    and a text in ancient Greek --
    and Demotic as well,
  • 5:29 - 5:32
    that wasn't quite so much of interest.
  • 5:32 - 5:36
    So this allowed us to translate
    hieroglyphs into ancient Greek,
  • 5:36 - 5:39
    a language that people
    did know to understand.
  • 5:39 - 5:42
    This now makes the task very simple.
  • 5:42 - 5:46
    All we need to do is to find
    the "Rosetta Stone" for the brain, right?
  • 5:46 - 5:47
    It sounds easy.
  • 5:47 - 5:49
    Where is it? Where do we
    have to go and dig?
  • 5:49 - 5:53
    Do we have to go and dig
    in North Africa or Southeast Asia?
  • 5:53 - 5:55
    Where is the "Rosetta Stone"
    for the brain going to be?
  • 5:55 - 6:00
    Nobody so far unfortunately has found
    the "Rosetta Stone" for the brain.
  • 6:00 - 6:05
    The reason is it is very very complicated,
    much more complicated than hieroglyphs.
  • 6:05 - 6:10
    We need to use something different,
    something called codebreaking.
  • 6:10 - 6:16
    Now, in the Second World War, the Germans
    thought they were particularly clever
  • 6:16 - 6:19
    by encrypting their messages
    on this famous Enigma machine.
  • 6:19 - 6:22
    They took a military text,
    they put it through the machine,
  • 6:22 - 6:26
    and out came some scrambled version
    that nobody could understand.
  • 6:26 - 6:30
    Then in the U-boats they
    would find a scrambled text,
  • 6:30 - 6:33
    and they put it through the machine,
    out they'd get the real message.
  • 6:33 - 6:36
    This is what you can do
    if you know the code.
  • 6:36 - 6:40
    The British were trying to decipher it,
    but they didn't know the code.
  • 6:40 - 6:43
    It was said they invented
    brute force, statistical techniques
  • 6:43 - 6:47
    that allowed them to translate
    this hidden code,
  • 6:47 - 6:50
    and that's what we do today
    with brain images.
  • 6:50 - 6:53
    We try to understand
    what the thoughts are a person has.
  • 6:53 - 6:55
    How does this work in detail?
  • 6:55 - 6:57
    l'll just give you a simple example.
  • 6:57 - 7:00
    What you can see here
    are three images on the left
  • 7:00 - 7:03
    the person was looking at
    inside the brain scanner:
  • 7:03 - 7:06
    the Brandenburg Gate, a bouquet
    of flowers and a German shepherd dog.
  • 7:06 - 7:10
    On the right are the corresponding
    patterns of the brain activity.
  • 7:10 - 7:12
    As you can see they are very different.
  • 7:12 - 7:17
    Every thought you have has its own
    unique signature pattern of activity
  • 7:17 - 7:18
    in your brain.
  • 7:18 - 7:21
    You think one thing,
    you get one pattern of activity;
  • 7:21 - 7:24
    you think something else,
    you get a different pattern of activity.
  • 7:24 - 7:26
    Now what we do is we train computers
  • 7:26 - 7:29
    to recognize these patterns
    of brain activity.
  • 7:29 - 7:32
    If I know to recognize
    the pattern of activity in the top right,
  • 7:32 - 7:36
    I can tell that the person is thinking
    about the Brandenburg Gate,
  • 7:36 - 7:40
    similar to recognizing an individual
    based on their fingerprints.
  • 7:40 - 7:43
    If I find their fingerprints,
    and I have them in a database,
  • 7:43 - 7:46
    I can use the software to detect
    the fingerprints out of our database.
  • 7:46 - 7:47
    That's what we do.
  • 7:47 - 7:50
    We train the computers;
    we train them to recognize
  • 7:50 - 7:52
    these brain activity patterns,
  • 7:52 - 7:55
    and then the computer has to prove
    that it's worth the money,
  • 7:55 - 7:58
    or if the program we write
    is worth its money,
  • 7:58 - 8:00
    that it can decipher
    what you are thinking about,
  • 8:00 - 8:03
    and then you give the computer
    some pattern of brain activity;
  • 8:03 - 8:05
    you might not know what it is,
  • 8:05 - 8:10
    and the proof is if the computer can
    correctly tell what you're thinking about.
  • 8:10 - 8:13
    This works remarkably well.
  • 8:13 - 8:18
    If you do this simple game,
    you get accuracy of up to 100%.
  • 8:18 - 8:20
    You get it right almost every time.
  • 8:20 - 8:24
    So this is for people in brain scanners
    looking at visual images.
  • 8:24 - 8:26
    But you could say,
  • 8:26 - 8:28
    "If someone's in a brain scanner
    looking at an image,
  • 8:28 - 8:31
    I just have to look at the image
    they're looking at
  • 8:31 - 8:33
    and I'll know what
    they're thinking about."
  • 8:33 - 8:35
    So, we need to go one step further.
  • 8:35 - 8:38
    The next step is we just
    have to imagine an image.
  • 8:38 - 8:42
    Put them in a brain scanner,
    we get them to imagine various things,
  • 8:42 - 8:46
    for example, watches, hands,
    faces, all sorts of stuff,
  • 8:46 - 8:49
    we measure the brain activity patterns,
    and we can decode
  • 8:49 - 8:52
    what they're thinking about
    based on pure imagination.
  • 8:52 - 8:55
    It's just in their mind,
    there's nothing in their environment
  • 8:55 - 8:59
    or on the computer screen to give it away,
    they're just thinking about it.
  • 8:59 - 9:02
    This works incredibly well, as well.
  • 9:02 - 9:03
    But you could say,
  • 9:03 - 9:08
    "This is still rather academic. Let's look
    for something even more interesting.
  • 9:08 - 9:10
    What about people's behavior,
    their decisions,
  • 9:10 - 9:11
    things that are relevant?"
  • 9:11 - 9:14
    So we went ahead
    and did a number of studies
  • 9:14 - 9:16
    where we tried to look
    at people's decisions.
  • 9:16 - 9:18
    These are the decisions,
    very simple decisions
  • 9:18 - 9:22
    among a few alternatives
    for things either completely irrelevant,
  • 9:22 - 9:23
    such as, for example:
  • 9:23 - 9:26
    "Do you want to press
    left or right button?",
  • 9:26 - 9:28
    or things that are a bit
    more relevant, for example:
  • 9:28 - 9:31
    "Do you like this car?
    Do you want to buy it?",
  • 9:31 - 9:33
    or "Do you like this car?
    Do you want to buy it?"
  • 9:33 - 9:37
    So we read the brain activity
    out of their brains.
  • 9:37 - 9:40
    In the first case, we looked
    after they've made up their mind.
  • 9:40 - 9:43
    So people make up their mind,
    we read their brain activity,
  • 9:43 - 9:46
    we try to decipher
    until which choice they've made.
  • 9:46 - 9:49
    So everyone of you make a choice,
  • 9:49 - 9:53
    say, for example, between wanting
    a BMW or a Mercedes.
  • 9:53 - 9:54
    You make your choice.
  • 9:54 - 9:56
    Can we read this
    out of your brain activity?
  • 9:56 - 10:00
    The answer is yes,
    with pretty decent accuracy.
  • 10:00 - 10:05
    The next question is, however,
    what about the choice itself?
  • 10:05 - 10:08
    You're more or less free to choose
    between one or the other.
  • 10:08 - 10:11
    What made you go one or the other way?
  • 10:11 - 10:15
    So we look backwards in time
    before the decision.
  • 10:15 - 10:18
    And what we found was
    that you could, to some degree,
  • 10:18 - 10:21
    predict a person's decision --
    a free decision,
  • 10:21 - 10:23
    they can choose either alternative --
  • 10:23 - 10:27
    before they actually feel
    that they're making up their mind,
  • 10:27 - 10:31
    up to 7 seconds before they think
    they're making up their mind.
  • 10:31 - 10:35
    So you think you're deciding now,
    but your brain has at least started
  • 10:35 - 10:39
    preparing this decision 7 seconds before.
  • 10:39 - 10:40
    How is that possible?
  • 10:40 - 10:44
    Well, it raises an important riddle.
  • 10:44 - 10:46
    That is, we normally think
  • 10:46 - 10:48
    of the sequence of events
    when we make choices,
  • 10:48 - 10:52
    we decide in our mind,
    we don't tell anyone, we just decide,
  • 10:52 - 10:55
    and then we use our brain
    to put our body into motion,
  • 10:55 - 10:58
    for example, to tell people
    what we're thinking about.
  • 10:58 - 11:00
    But this says it's quite different.
  • 11:00 - 11:04
    This says the brain
    starts preparing the decision,
  • 11:04 - 11:07
    and then your mind comes
    in a few seconds later,
  • 11:07 - 11:10
    and then you start moving
    and doing things.
  • 11:10 - 11:15
    This is quite different, and it raises
    lots of interesting questions.
  • 11:15 - 11:20
    The most important one is:
    Who's responsible for the action?
  • 11:20 - 11:23
    If your conscious mind comes
    after the decision,
  • 11:23 - 11:25
    that presumably has already been made,
  • 11:25 - 11:28
    how can you be held responsible
    for the action?
  • 11:28 - 11:31
    If you commit a crime,
    it was my unconscious brain activity
  • 11:31 - 11:34
    that happened before I made up my mind,
  • 11:34 - 11:37
    it's not my fault
    that I committed this crime,
  • 11:37 - 11:38
    you could say.
  • 11:38 - 11:42
    So you can see there are lots
    of interesting questions raised here
  • 11:42 - 11:44
    with respect to free will.
  • 11:44 - 11:47
    I'm going to leave that as an open teaser.
  • 11:47 - 11:49
    I'm going to focus
    on a different question.
  • 11:49 - 11:52
    If you're interested in that,
    go to our website.
  • 11:52 - 11:54
    I'm going to ask
    a different question, and that is:
  • 11:54 - 11:58
    Can we read people's minds
    in a technology
  • 11:58 - 12:02
    that is similar now to these stage acts
    that people did in the 19th century?
  • 12:02 - 12:05
    What you can see here
    is a depiction of a stage act,
  • 12:05 - 12:08
    a magician draws a person
    from the audience,
  • 12:08 - 12:11
    they come on the stage and are blindfolded
    and think about something,
  • 12:11 - 12:14
    say, for example, a shape or a person,
  • 12:14 - 12:16
    and the magician can
    magically read their mind
  • 12:16 - 12:20
    and draw their thought on the board here.
  • 12:20 - 12:23
    Can we now replace this stage act
    with something new?
  • 12:23 - 12:25
    Can we put a brain scanner on the stage?
  • 12:25 - 12:28
    And then the famous brain scanner,
    you put people in it,
  • 12:28 - 12:31
    and it shows you on a board
    what they're thinking about.
  • 12:31 - 12:33
    Is this possible?
  • 12:33 - 12:37
    The answer is: to some degree,
    but not that well.
  • 12:37 - 12:39
    I'll explain to you why.
  • 12:39 - 12:43
    First of all, there's severe limitation
    with the resolution of brain scanners.
  • 12:43 - 12:45
    They have a resolution
    of a few millimeters,
  • 12:45 - 12:49
    so that means in every one of these
    small measurement volumes we have,
  • 12:49 - 12:51
    we have up to a million nerve cells.
  • 12:51 - 12:55
    That's a lot of nerve cells
    in one measurement pixel.
  • 12:55 - 13:00
    So basically we need to increase
    the resolution of these brain scanners,
  • 13:00 - 13:03
    so we can get down
    to the activity of single cells,
  • 13:03 - 13:06
    if you really want
    to read out the full details,
  • 13:06 - 13:09
    but there are even worse issues
    in this than just the resolution.
  • 13:09 - 13:14
    One big problem is that everyone of you
    has that own signature brain language
  • 13:14 - 13:16
    that stores information.
  • 13:16 - 13:18
    You can see here 4 brain activity patterns
  • 13:18 - 13:21
    for the same thought
    in 4 different individuals.
  • 13:21 - 13:22
    They're all different.
  • 13:22 - 13:25
    Everyone stores information differently,
  • 13:25 - 13:29
    which explains why we have
    such a hard time understanding each other,
  • 13:29 - 13:32
    if our brain activity patterns
    are so different.
  • 13:32 - 13:34
    So this is a severe challenge.
  • 13:34 - 13:36
    So we can't train our machine
    on one person
  • 13:36 - 13:38
    and use it for another person.
  • 13:38 - 13:42
    It doesn't work that well
    on the second person.
  • 13:42 - 13:44
    Another problem is:
  • 13:44 - 13:47
    The preferences and thoughts
    change on the brain language
  • 13:47 - 13:50
    presumably changes
    well across the lifespan.
  • 13:50 - 13:53
    When you're young
    your favorite movie might be Lassie,
  • 13:53 - 13:56
    your favorite food might be a hamburger,
  • 13:56 - 13:58
    and your favorite music
    might have been heavy metal.
  • 13:58 - 14:03
    Come on, we're talking about secrets here.
    That's your secret, my secret.
  • 14:03 - 14:08
    When you're older, things might change,
    now you like schmaltzy Austrian movies,
  • 14:08 - 14:11
    you like salad or at least pretend
    to yourself that you like salad
  • 14:11 - 14:13
    and Bavarian brass music.
  • 14:13 - 14:15
    Come one, admit it.
  • 14:15 - 14:18
    So the problem is
    that the brain activity patterns
  • 14:18 - 14:22
    causing this kind of information
    change across a lifespan,
  • 14:22 - 14:24
    and we got no way of dealing with this.
  • 14:24 - 14:29
    But now the biggest problem is that we
    can think so many different things.
  • 14:29 - 14:31
    One of my favorite sentences
    is from Monty Python,
  • 14:31 - 14:34
    it's called, "My hovercraft
    is full of eels."
  • 14:34 - 14:38
    Who would've ever thought that
    someone was going to think this today?
  • 14:38 - 14:40
    If you're to program
    the computer to predict
  • 14:40 - 14:42
    what you might be thinking about today,
  • 14:42 - 14:44
    I'm pretty sure
    "My hovercraft is full of eels"
  • 14:44 - 14:47
    would've been very low on that list.
  • 14:47 - 14:51
    So we need to be able to account
    for these situations as well.
  • 14:51 - 14:53
    We can think so many different things.
  • 14:53 - 14:56
    We could take a whole dictionary
    full of different things.
  • 14:56 - 14:59
    So, we need a dictionary to translate
    thoughts into brain activity patterns,
  • 14:59 - 15:01
    and we don't have this dictionary.
  • 15:01 - 15:04
    So, what could this look like?
  • 15:04 - 15:06
    Do we get a subject to come,
    we pay them very well,
  • 15:06 - 15:09
    they come for 20 years
    to the brain scanner.
  • 15:09 - 15:11
    The first day we start
    reading the dictionary.
  • 15:11 - 15:16
    We begin with apple, and we continue,
    and after 20 years we've finally done,
  • 15:16 - 15:19
    but with zed, we'd start
    reading zebra and etc.
  • 15:19 - 15:21
    Is that how we measure
    the brain activity patterns
  • 15:21 - 15:24
    for all these thoughts they might have?
  • 15:24 - 15:27
    Well, luckily we can take a shortcut.
  • 15:27 - 15:31
    The shortcut is that the brain’s
    arranged information in a way
  • 15:31 - 15:34
    that is easier for us to understand.
  • 15:34 - 15:37
    And that is it uses
    principles of similarity,
  • 15:37 - 15:40
    and I explain to you how this works.
  • 15:40 - 15:43
    You can see in the top right
    a hypothetical brain activity pattern
  • 15:43 - 15:47
    while the person is thinking about a car,
    and the bottom right,
  • 15:47 - 15:51
    a hypothetical brain activity pattern
    while they're thinking about a bike.
  • 15:51 - 15:54
    But now we've measured,
    with a brain scanner, a different pattern.
  • 15:54 - 15:58
    It looks like a mixture for the pattern
    of a car and the pattern of a bike.
  • 15:58 - 16:01
    What could that be?
    What do you think?
  • 16:01 - 16:04
    Well, it's a motorbike.
  • 16:04 - 16:07
    So you can exploit
    these principles of similarity.
  • 16:07 - 16:11
    You don't need to know
    what every thought looks like in the brain
  • 16:11 - 16:14
    and you can still read out
    a large number of thoughts.
  • 16:14 - 16:18
    Now there are a number
    of technical issues ensuing from this.
  • 16:18 - 16:22
    For example, potential lie detectors
    or brain marketing,
  • 16:22 - 16:25
    lots of people are interested
    in commercial applications
  • 16:25 - 16:27
    or forensic applications
    of this technology,
  • 16:27 - 16:32
    and medical applications allowing people
    who can't move their bodies
  • 16:32 - 16:35
    to suddenly move and control computers
    and do things like that.
  • 16:35 - 16:37
    Now there's a big debate necessary
  • 16:37 - 16:43
    about what of these technologies we want
    and what we think is ethically feasible.
  • 16:43 - 16:46
    But one important question
    people are always interested in is:
  • 16:46 - 16:50
    Does that mean now
    you open to manipulation?
  • 16:50 - 16:54
    Well, don't worry about that too much
    because first of all, it would mean
  • 16:54 - 16:57
    that you could have to put someone
    inside a brain scanner.
  • 16:57 - 16:59
    So to some degree,
    your thoughts are private.
  • 16:59 - 17:01
    If you're just walking through the world,
  • 17:01 - 17:04
    nobody has a mobile brain scanner
    that works remotely.
  • 17:04 - 17:06
    You can think about your PIN
    of your credit card,
  • 17:06 - 17:10
    nobody is going to be able to read it out.
    Don't worry about that.
  • 17:10 - 17:13
    Now, one thing that people
    are still quite interested in
  • 17:13 - 17:18
    is whether you can be manipulated,
    "manipulated" here means:
  • 17:18 - 17:21
    Is it possible to write thoughts
    into a person's brain
  • 17:21 - 17:22
    to make them think certain things
  • 17:22 - 17:25
    as you can see
    in some science fiction movies
  • 17:25 - 17:27
    like in "Strange Days,"
    or "Inception," and etc.?
  • 17:27 - 17:32
    The answer is today this is not possible.
  • 17:32 - 17:36
    And the reason is that the way
    our thoughts are coded in our brain
  • 17:36 - 17:40
    is in very intricate fine grain patterns
    of brain activity,
  • 17:40 - 17:46
    there's really lots of detail
    in these brain activity patterns.
  • 17:46 - 17:49
    Today, there are techniques
    for stimulating the brain,
  • 17:49 - 17:52
    but they're very diffuse;
  • 17:52 - 17:55
    there's no technique available
    that would allow us to write
  • 17:55 - 17:59
    these very detailed patterns
    of activity into the brain.
  • 17:59 - 18:04
    So, brain scanners can be used to read out
    a person's thoughts to some degree.
  • 18:04 - 18:07
    Don't worry about the technology,
  • 18:07 - 18:10
    and especially you don't have to worry
    about people programming thoughts
  • 18:10 - 18:12
    into your brains.
  • 18:12 - 18:13
    Thanks very much.
  • 18:13 - 18:15
    (Applause)
Title:
Mind reading with brain scanners | John-Dylan Hayes | TEDxBerlin
Description:

This talk was given at a local TEDx event, produced independently of the TED Conferences.

The research of John-Dylan Haynes focuses on the neural mechanisms underlying human cognitive processes. His special interests are technical and ethical foundations of mental state decoding, as well as the neuroscience of consciousness, intentions and free will. He talks about mind reading with brain scanners.

more » « less
Video Language:
English
Team:
closed TED
Project:
TEDxTalks
Duration:
18:22

English subtitles

Revisions Compare revisions